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Displaying results 1 to 25 of 49.

  1. Ontology of Communication
    Agent-Based Data-Driven or Sign-Based Substitution-Driven?
    Author: Hausser, Roland
    Published: 2023
    Publisher:  Springer International Publishing AG, Cham

    The book gives a comprehensive discussion of Database Semantics (DBS) as an agent-based data-driven theory of how natural language communication essentially works. In language communication, agents switch between speak mode, driven by... more

     

    The book gives a comprehensive discussion of Database Semantics (DBS) as an agent-based data-driven theory of how natural language communication essentially works. In language communication, agents switch between speak mode, driven by cognition-internal content (input) resulting in cognition-external raw data (e.g. sound waves or pixels, which have no meaning or grammatical properties but can be measured by natural science), and hear mode, driven by the raw data produced by the speaker resulting in cognition-internal content.The motivation is to compare two approaches for an ontology of communication: agent-based data-driven vs. sign-based substitution-driven. Agent-based means: design of a cognitive agent with (i) an interface component for converting raw data into cognitive content (recognition) and converting cognitive content into raw data (action), (ii) an on-board, content-addressable memory (database) for the storage and content retrieval, (iii) separate treatments of the speak and the hear mode. Data-driven means: (a) mapping a cognitive content as input to the speak-mode into a language-dependent surface as output, (b) mapping a surface as input to the hear-mode into a cognitive content as output. Oppositely, sign-based means: no distinction between speak and hear mode, whereas substitution-driven means: using a single start symbol as input for generating infinitely many outputs, based on substitutions by rewrite rules.Collecting recent research of the author, this beautiful, novel and original exposition begins with an introduction to DBS, makes a linguistic detour on subject/predicate gapping and slot-filler repetition, and moves on to discuss computational pragmatics, inference and cognition, grammatical disambiguation and other related topics. The book is mostly addressed to experts working in the field of computational linguistics, as well as to enthusiasts interested in the history and early development of this subject, starting with the pre-computational foundations of theoretical computer science and symbolic logic in the 30s

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9783031227387
    Edition: 1st ed. 2023
    Subjects: Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Expert Systems; Computational linguistics; Computerlinguistik und Korpuslinguistik; Expert systems / knowledge-based systems; Künstliche Intelligenz; LANGUAGE ARTS & DISCIPLINES / Linguistics; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 258 Seiten
    Notes:

    1. Introduction 1.1 Ontology 1.2 Computational Cognition1.3 Agent-Based Data-Driven vs. Sign-Based Substitution-Driven 1.4 Reconciling the Hierarchical and the Linear 1.5 Speak Mode Converts Hierarchy into Linear Surface 1.6 Hear Mode Re-Converts Linear Input into Hierarchical Output 1.7 Derivation Order 1.8 Type Transparency 1.9 Four Kinds of Type-Token Relations 1.10 Conclusion 2. Laboratory Set-up of Database Semantics 2.1 Early Times 2.2 Study of the Language Signs 2.3 Using Successful Communication for the Laboratory Set-Up 2.4 From Operational Implementation to Declarative Specification 2.5 Formal Fragments of Natural Language 2.6 Incremental Upscaling Cycles 2.7 Conclusion 3. Outline of DBS 3.1 Building Content in the Agent's Hear Mode3.2 Storage and Retrieval of Content in the On-Board Memory 3.3 Speak Mode Riding Piggyback on the Think Mode 3.4 Component Structure of Cognition 3.5 Sensory Media, Processing Media, and Their Modalities 3.6 Reference as a Purely Cognitive Process 3.7 Grounding 3.8 Conclusion 4. Software Mechanisms of the Content Kinds 4.1 Apparent Terminological Redundancy4.2 Restriction of Figurative Use to Concepts 4.3 Additional Constraint on Figurative Use 4.4 Declarative Specification Of Concepts for Recognition 4.5 Declarative Specification of Concepts for Action4.6 Indirect Grounding of Indexicals and Names 4.7 Conclusion 5. Comparison of Coordination and Gapping 5.1 Coordination of Elementary Adnominals 5.2 Coordination of Phrasal Adnominal Modifiers 5.3 Coordination of Phrasal Adverbial Modifiers 5.4 Coordination of Elementary Nouns as Subject 5.5 Intra- and Extrapropositional Verb Coordination 5.6 Extrasentential Coordination 5.7 Quasi Coordination in Subject Gapping 5.8 Quasi Coordination in Predicate Gapping 5.9 Quasi Coordination in Object Gapping 5.10 Conclusion 6. Are Iterating Slot-Filler Structures Universal? 6.1 Language and Thought 6.2 Slot-Filler Iteration 6.3 Marked Slot-Filler Repetition in Infinitives6.4 Marked Slot-Filler Repetition in Object Clauses 6.5 Marked Slot-Filler Repetition in Adnominal Clauses 6.6 Unmarked Slot-Filler Iteration in Gapping Constructions 6.7 Long-Distance Dependency 6.8 Conclusion 7. Computational Pragmatics7.1 Four Kinds of Content in DBS 7.2 Coactivation Resulting in Resonating Content 7.3 Literal Pragmatics of Adjusting Perspective7.4 Nonliteral Pragmatics of Syntactic Mood Adaptation 7.5 Nonliteral Pragmatics of Figurative Use7.6 Conclusion8. Discontinuous Structures in DBS and PSG8.1 The Time-Linear Structure of Natural Language 8.2 Constituent Structure Paradox of PSG8.3 Suspension in Database Semantics 8.4 Discontinuity with and without Suspension in DBS 8.5 Conclusion 9. Classical Syllogisms as Computational Inferences 9.1 Logical vs. Common Sense Reasoning9.2 Categorical Syllogisms 9.3 Modus Ponendo Ponens 9.4 Modus Tollendo Tollens 9.5 Modi BARBARA and CELARENT9.6 Modi DARII and FERIO 9.7 Modi BAROCO and BOCARDO 9.8 Combining S- and C-Inferencing 9.9 Analogy 9.10 Conclusion 10. Grounding of Concepts in Science 10.1 The Place of Concepts in a Content 10.2 Definition of Concepts at the Elementary, Phrasal, or Clausal Level? 10.3 Extending a Concept to its Class 10.4 Language Communication10.5 Combining Concepts into Content 10.6 Language Surfaces and Meaning_1 Concepts in Communication 10.7 Extero- and Interoception 10.8 Emotion 10.9 Conclusion 11. Function Words 11.1 Introduction11.2 Interpreting Determiner Noun Combination in Hear Mode 11.3 Producing Dete
  2. Vector Semantics
    Author: Kornai, Andras
    Published: 2023
    Publisher:  Springer Verlag, Singapore, Singapore

    This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics.The computational linguists and deep learning researchers who developed word vectors have relied primarily on the... more

     

    This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics.The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use.In spite of the fact that these two schools both have 'linguistics' in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9789811956065
    Edition: 1st ed. 2023
    Series: Cognitive Technologies
    Subjects: Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Expert Systems; Computational linguistics; Computer-Anwendungen in Kunst und Geisteswissenschaften; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Computerlinguistik und Korpuslinguistik; Expert systems / knowledge-based systems; Künstliche Intelligenz; LANGUAGE ARTS & DISCIPLINES / Library & Information Science; LANGUAGE ARTS & DISCIPLINES / Linguistics; Literature: history & criticism; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 273 Seiten
    Notes:

    Interessenniveau: 06, Professional and scholarly: For an expert adult audience, including academic research. (06)

    Contents Preface............................................................... vii1 Foundations of non-compositionality................................. 1.1 Background ................................................... 1.2 Lexicographic principles ........................................ 1.3 The syntax of definitions ........................................ 1.4 The geometry of definitions...................................... 1.5 The algebra of definitions ....................................... 2 From morphology to syntax ........................................ 23 2.1 Lexical categories and subcategories .............................. 23 2.2 Bound morphemes ............................................. 25 2.3 Relations ..................................................... 30 2.4 Linking....................................................... 39 2.5 Naive grammar ................................................ 463 Time and space.................................................... 53 3.1 Space ........................................................ 54 3.2 Time ......................................................... 59 3.3 Indexicals, coercion ............................................ 62 3.4 Measure ...................................................... 654 Negation.......................................................... 69 4.1 Negation in the lexicon.......................................... 71 4.2 Quantifiers .................................................... 73 4.3 Negation in compositional constructions ........................... 74 4.4 Double negation ............................................... 77 4.5 Compositional quantifiers ....................................... 78 4.6 Disjunction ................................................... 80 4.7 Scope ambiguities.............................................. 81 4.8 Conclusions ................................................... 82 5 Valuations ........................................................ 83 5.1 Introduction ................................................... 83 5.2 The likeliness scale............................................. 84 5.3 Naive inference (likeliness update) ................................ 86 5.4 Learning...................................................... 89 5.5 Conclusions ................................................... 916 Modality ......................................................... 93 6.1 The deontic world .............................................. 93 6.2 Epistemic and autoepistemic logic ................................ 93 6.3 Defaults ...................................................... 937 Adjectives, gradience, implicature ................................... 95 7.1 Adjectives .................................................... 95 7.2 Gradience..................................................... 96 7.3 Implicature.................................................... 96 7.4 The elementary pieces .......................................... 97 7.5 The mechanism ................................................ 100 7.6 Memory ...................................................... 103 7.7 Conclusions ................................................... 1048 Trainability and real-world knowledge............................... 1078.1 Proper names.................................................. 107 8.2 Trainability ................................................... 1099 Dynamic embeddings ....................................
  3. Vector Semantics
    Author: Kornai, Andras
    Published: 2023
    Publisher:  Springer Verlag, Singapore, Singapore

    This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics.The computational linguists and deep learning researchers who developed word vectors have relied primarily on the... more

     

    This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics.The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use.In spite of the fact that these two schools both have 'linguistics' in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings

     
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    Content information
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9789811956096
    Edition: 1st ed. 2023
    Series: Cognitive Technologies
    Subjects: Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Expert Systems; Computational linguistics; Computer-Anwendungen in Kunst und Geisteswissenschaften; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Computerlinguistik und Korpuslinguistik; Expert systems / knowledge-based systems; Künstliche Intelligenz; LANGUAGE ARTS & DISCIPLINES / Library & Information Science; LANGUAGE ARTS & DISCIPLINES / Linguistics; Literature: history & criticism; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 273 Seiten
    Notes:

    Interessenniveau: 06, Professional and scholarly: For an expert adult audience, including academic research. (06)

    Contents Preface............................................................... vii1 Foundations of non-compositionality................................. 1.1 Background ................................................... 1.2 Lexicographic principles ........................................ 1.3 The syntax of definitions ........................................ 1.4 The geometry of definitions...................................... 1.5 The algebra of definitions ....................................... 2 From morphology to syntax ........................................ 23 2.1 Lexical categories and subcategories .............................. 23 2.2 Bound morphemes ............................................. 25 2.3 Relations ..................................................... 30 2.4 Linking....................................................... 39 2.5 Naive grammar ................................................ 463 Time and space.................................................... 53 3.1 Space ........................................................ 54 3.2 Time ......................................................... 59 3.3 Indexicals, coercion ............................................ 62 3.4 Measure ...................................................... 654 Negation.......................................................... 69 4.1 Negation in the lexicon.......................................... 71 4.2 Quantifiers .................................................... 73 4.3 Negation in compositional constructions ........................... 74 4.4 Double negation ............................................... 77 4.5 Compositional quantifiers ....................................... 78 4.6 Disjunction ................................................... 80 4.7 Scope ambiguities.............................................. 81 4.8 Conclusions ................................................... 82 5 Valuations ........................................................ 83 5.1 Introduction ................................................... 83 5.2 The likeliness scale............................................. 84 5.3 Naive inference (likeliness update) ................................ 86 5.4 Learning...................................................... 89 5.5 Conclusions ................................................... 916 Modality ......................................................... 93 6.1 The deontic world .............................................. 93 6.2 Epistemic and autoepistemic logic ................................ 93 6.3 Defaults ...................................................... 937 Adjectives, gradience, implicature ................................... 95 7.1 Adjectives .................................................... 95 7.2 Gradience..................................................... 96 7.3 Implicature.................................................... 96 7.4 The elementary pieces .......................................... 97 7.5 The mechanism ................................................ 100 7.6 Memory ...................................................... 103 7.7 Conclusions ................................................... 1048 Trainability and real-world knowledge............................... 1078.1 Proper names.................................................. 107 8.2 Trainability ................................................... 1099 Dynamic embeddings ....................................
  4. Wineinformatics
    A New Data Science Application
    Author: Chen, Bernard
    Published: 2022
    Publisher:  Springer Verlag, Singapore, Singapore

    Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and... more

     

    Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data.This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors.This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book

     
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  5. Artificial Intelligence for Beginners
    A Beginner's Guide to Understanding AI and Its Impact on Society (2023 Crash Course)
    Author: Woolery, Nathaniel
    Published: 2023
    Publisher:  Nathaniel Woolery, [Erscheinungsort nicht ermittelbar]

  6. Advances in information retrieval
    Part 1
    Contributor: Caputo, Annalina (HerausgeberIn); Crestani, Fabio (HerausgeberIn); Davis, Brian (HerausgeberIn); Goeuriot, Lorraine (HerausgeberIn); Gurrin, Cathal (HerausgeberIn); Joho, Hideo (HerausgeberIn); Kamps, Jaap (HerausgeberIn); Kruschwitz, Udo (HerausgeberIn); Maistro, Maria (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer International Publishing AG, Cham

    The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(13980)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    The three-volume set LNCS 13980, 13981 and 13982 constitutes the refereed proceedings of the 45th European Conference on IR Research, ECIR 2023, held in Dublin, Ireland, during April 2-6, 2023. The 65 full papers, 41 short papers, 19 demonstration papers, and 12 reproducibility papers, 10 doctoral consortium papers were carefully reviewed and selected from 489 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Caputo, Annalina (HerausgeberIn); Crestani, Fabio (HerausgeberIn); Davis, Brian (HerausgeberIn); Goeuriot, Lorraine (HerausgeberIn); Gurrin, Cathal (HerausgeberIn); Joho, Hideo (HerausgeberIn); Kamps, Jaap (HerausgeberIn); Kruschwitz, Udo (HerausgeberIn); Maistro, Maria (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031282430
    Parent title: Advances in information retrieval - Show all bands
    Corporations / Congresses: European Conference on Information Retrieval, 45. (2023, Dublin)
    Series: Lecture notes in computer science ; 13980
    Subjects: COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Data Processing / Storage & Retrieval; COMPUTERS / Database Management / Data Mining; COMPUTERS / Database Management / General; Data Mining; Data Warehousing; Data mining; Databases; Datenbanken; Information retrieval; Informationsrückgewinnung, Information Retrieval; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: xlvii, 740 Seiten
    Notes:

    Full Papers.- Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval.- User Requirement Analysis for a Recommender System-Based Meeting Assistant.- Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering.- Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation.- Injecting the BM25 Score as Text Improves BERT-Based Re-rankers.- Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers.- A Knowledge Infusion based Multitasking System for Sarcasm Detection in Meme.- Multilingual Detection of Check-Worthy Claims using World Languages and Adapter Fusion.- Market-Aware Models for Efficient Cross Market Recommendation.- TourismNLG: A Multi-lingual Generative Benchmark for the Tourism Domain.- An Interpretable Knowledge Representation Framework for Natural Language Processing with Cross-Domain Application.- Graph-based Recommendation for Sparse and Heterogeneous User Interactions.- It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers.- Recommendation Algorithm Based on Deep Light Graph Convolution Network in Knowledge Graph.- Query Performance Prediction for Neural IR: Are We There Yet?.- Item Graph Convolutional Collaborative Filtering for Inductive Recommendations.- CoLISA: Inner Interaction via Contrastive Learning for Multi-Choice Reading Comprehension.- Viewpoint Diversity in Search Results.- COILCR: Efficient Semantic Matching in Contextualized Exact Match Retrieval.- Bootstrapped nDCG Estimation in the Presence of Unjudged Documents.- Predicting the Listening Contexts of Music Playlists Using Knowledge Graphs.- Keyword Embeddings for Query Suggestion.- Domain-driven and Discourse-guided Scientific Summarisation.- Injecting Temporal-aware Knowledge in Historical Named Entity Recognition.- A Mask-based Logic Rules Dissemination Method for Sentiment Classifiers.- Contrasting Neural Click Models and Pointwise IPS Rankers.- Sentence Retrieval for Open-Ended Dialogue using Dual Contextual Modeling.- Temporal Natural Language Inference: Evidence-based Evaluation of Temporal Text Validity.- Theoretical Analysis on the Efficiency of Interleaved Comparisons.- Intention-aware Neural Networks for Question Paraphrase Identification.- Automatic and Analytical Field Weighting for Structured Document Retrieval.- An Experimental Study on Pretraining Transformers from Scratch for IR.- Neural Approaches to Multilingual Information Retrieval.- CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval.- SR-CoMbEr: Heterogeneous Network Embedding using Community Multi-view Enhanced Graph Convolutional Network for Automating Systematic Reviews.- Multimodal Inverse Cloze Task for Knowledge-based Visual Question Answering.- A Transformer-based Framework for POI-level Social Post Geolocation.- Document-Level Relation Extraction with Distance-dependent Bias Network and Neighbors Enhanced Loss.- Investigating Conversational Agent Action in Legal Case Retrieval.- MS-Shift: An Analysis of MS MARCO Distribution Shifts on Neural Retrieval.- Listwise Explanations for Ranking Models using Multiple Explainers.- Improving video retrieval using multilingual knowledge transfer.- Service is good, very good or excellent? Towards Aspect based Sentiment Intensity Analysis.- Effective Hierarchical Information Threading using Network Community Detection.- HADA: A Graph-based Amalgamation Framework in Image-Text Retrieval.
  7. Computational linguistics and intelligent text processing
    20th International Conference, CICLing 2019, La Rochelle, France, April 7-13, 2019, revised selected papers
    Contributor: Gelbukh, Alexander (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Inter-library loan:
    No inter-library loan

     

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected from 335 submissions. The book also contains 3 invited papers.The papers are organized in the following topical sections: General, Information extraction, Information retrieval, Language modeling, Lexical resources, Machine translation, Morphology, sintax, parsing, Name entity recognition, Semantics and text similarity, Sentiment analysis, Speech processing, Text categorization, Text generation, and Text mining

     
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    Source: Union catalogues
    Contributor: Gelbukh, Alexander (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    Corporations / Congresses: CICLing, 20. (2019, La Rochelle)
    Series: Lecture notes in computer science
    Subjects: COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Data Processing / Storage & Retrieval; COMPUTERS / Database Management / Data Mining; COMPUTERS / Database Management / General; COMPUTERS / Programming / General; Computer programming / software development; Data Mining; Data Warehousing; Data mining; Databases; Datenbanken; Information retrieval; Informationsrückgewinnung, Information Retrieval; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Theoretische Informatik; Wissensbasierte Systeme, Expertensysteme
    Notes:

    Artificial intelligence.- Natural language processing.- Information extraction.- Lexical semantics.- Natural language generation.- Language resources.- Phonology .- Morphology.- Discourse.- Dialogue and pragmatics.
  8. Computational linguistics and intelligent text processing
    20th International Conference, CICLing 2019, La Rochelle, France, April 7-13, 2019, revised selected papers – Part 2
    Contributor: Gelbukh, Alexander (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(13452)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected from 335 submissions. The book also contains 3 invited papers.The papers are organized in the following topical sections: General, Information extraction, Information retrieval, Language modeling, Lexical resources, Machine translation, Morphology, sintax, parsing, Name entity recognition, Semantics and text similarity, Sentiment analysis, Speech processing, Text categorization, Text generation, and Text mining

     
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  9. Web and big data
    6th International Joint Conference, APWeb-WAIM 2022, Nanjing, China, November 25-27, 2022, proceedings – Part 2
    Contributor: Li, Bohan (HerausgeberIn); Yue, Lin (HerausgeberIn); Tao, Chuanqi (HerausgeberIn); Han, Xuming (HerausgeberIn); Calvanese, Diego (HerausgeberIn); Amagasa, Toshiyuki (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    This three-volume set, LNCS 13421, 13422 and 13423, constitutes the thoroughly refereed proceedings of the 6th International Joint Conference, APWeb-WAIM 2022, held in Nanjing, China, in August 2022.The 75 full papers presented together with 45 short... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(13422)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    This three-volume set, LNCS 13421, 13422 and 13423, constitutes the thoroughly refereed proceedings of the 6th International Joint Conference, APWeb-WAIM 2022, held in Nanjing, China, in August 2022.The 75 full papers presented together with 45 short papers, and 5 demonstration papers were carefully reviewed and selected from 297 submissions. The papers are organized around the following topics: Big Data Analytic and Management, Advanced database and web applications, Cloud Computing and Crowdsourcing, Data Mining, Graph Data and Social Networks, Information Extraction and Retrieval, Knowledge Graph, Machine Learning, Query processing and optimization, Recommender Systems, Security, privacy, and trust and Blockchain data management and applications, and Spatial and multi-media data

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Li, Bohan (HerausgeberIn); Yue, Lin (HerausgeberIn); Tao, Chuanqi (HerausgeberIn); Han, Xuming (HerausgeberIn); Calvanese, Diego (HerausgeberIn); Amagasa, Toshiyuki (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031251979
    Parent title: Web and big data : 6th International Joint Conference, APWeb-WAIM 2022, Nanjing, China, November 25-27, 2022, proceedings - Show all bands
    Corporations / Congresses: APWeb-WAIM, 6. (2022, Nanjing)
    Series: Lecture notes in computer science ; 13422
    Subjects: Bildverarbeitung; COMPUTERS / Computer Vision & Pattern Recognition; COMPUTERS / Data Processing / General; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Database Management / Data Mining; COMPUTERS / Database Management / General; COMPUTERS / Mathematical & Statistical Software; Computer vision; Data Mining; Data mining; Databases; Datenbanken; Discrete mathematics; Diskrete Mathematik; Mathematik für Informatiker; Maths for computer scientists; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wahrscheinlichkeitsrechnung und Statistik; Wissensbasierte Systeme, Expertensysteme
    Scope: xviii, 560 Seiten, Illustrationen
    Notes:

    Research tracks. Big Data Analytic and Management.- Advanced database and web applications.- Cloud Computing and Crowdsourcing.- Data Mining.- Graph Data and Social Networks.- Information Extraction and Retrieval.- Knowledge Graph.- Machine Learning.- Query processing and optimization.- Recommender Systems.- Security, privacy, and trust& Blockchain data management and applications.- Spatial and multi-media data.- Demo papers.
  10. Deep learning theory and applications
    4th International Conference, DeLTA 2023, Rome, Italy, July 13-14, 2023, proceedings
    Contributor: Conte, Donatello (HerausgeberIn); Fred, Ana (HerausgeberIn); Gusikhin, Oleg (HerausgeberIn); Sansone, Carlo (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023. The 9 full papers and 22 short papers presented were thoroughly... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RS 7445(1875)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

     

    This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023. The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Conte, Donatello (HerausgeberIn); Fred, Ana (HerausgeberIn); Gusikhin, Oleg (HerausgeberIn); Sansone, Carlo (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031390586
    Corporations / Congresses: DeLTA, 4. (2023, Rom)
    Series: Communications in computer and information science ; 1875
    Subjects: Angewandte Informatik; Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / General; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Database Management / Data Mining; COMPUTERS / Social Aspects / Human-Computer Interaction; Data Mining; Data mining; Information technology: general issues; Informationstechnik (IT), allgemeine Themen; Künstliche Intelligenz; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: xvii, 482 Seiten, Illustrationen, Diagramme
    Notes:

    Pervasive AI: (deep) Learning into the Wild.- Deep Reinforcement Learning to Improve Traditional Supervised Learning Methodologies.- Synthetic Network Traffic Data Generation and Classification of Advanced Persistent Threat Samples: A Case Study with GANs and XGBoost.- Improving Primate Sounds Classification Using Binary Presorting for Deep Learning.- Towards Exploring Adversarial Learning for Anomaly Detection in Complex Driving Scenes.- Dynamic Prediction of Survival Status in Patients Undergoing Cardiac Catheterization Using a Joint Modeling Approach.- A Machine Learning Framework for Shuttlecock Tracking and Player Service Fault Detection.- An Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Strategy and NLP-Driven.- Sentiment Analysis for Enhanced Forecasting Accuracy and Investor Insight.- Machine Learning Applied to Speech Recordings for Parkinson's Disease Recognition.- Vision Transformers for Galaxy Morphology Classification: Fine-Tuning Pre-Trained Networks vs. Training from Scratch.- A Study of Neural Collapse for Text Classification.- Research Data Reusability with Content-Based Recommender System.- MSDeepNet: A Novel Multi-Stream Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos.- A Novel Probabilistic Approach for Detecting Concept Drift in Streaming Data.- Explaining Relation Classification Models with Semantic Extents.- Phoneme-Based Multi-Task Assessment of Affective Vocal Bursts.- Using Artificial Intelligence to Reduce the Risk of Transfusion Hemolytic Reactions.- ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP.- Exploring ASR Models in Low-Resource Languages: Use-Case the Macedonian Language.- Facilitating Enterprise Model Classification via Embedding Symbolic Knowledge into Neural Network Models.- Explainable Abnormal Time Series Subsequence Detection Using Random Convolutional Kernels.- TaxoSBERT: Unsupervised Taxonomy Expansion Through Expressive Semantic Similarity.- Towards Equitable AI in HR: Designing a Fair, Reliable, and Transparent Human Resource Management Application.- An Explainable Approach for Early Parkinson Disease Detection Using Deep Learning.- UMLDesigner: An Automatic UML Diagram Design Tool.- Graph Neural Networks for Circuit Diagram Pattern Generation.- Generative Adversarial Networks for Domain Translation in Unpaired Breast DCE-MRI Datasets.- A Survey on Reinforcement Learning and Deep Reinforcement Learning for Recommender Systems.- GAN-Powered Model&Landmark-Free Reconstruction: A Versatile Approach for High-Quality 3D Facial and Object Recovery from Single Images.-GAN-Based LiDAR Intensity Simulation.- Evaluating Prototypes and Criticisms for Explaining Clustered Contributions in Digital Public Participation Processes.- FRLL-Beautified: A Dataset of Fun Selfie Filters with Facial Attributes.- CSR & Sentiment Analysis: A New Customized Dictionary.
  11. A.I. Survival Guide
    Artificial Intelligence Basics
    Author: Cusack, Cara; Cusack, Martin
    Published: 2023
    Publisher:  Ingramspark, [Erscheinungsort nicht ermittelbar]

  12. Introduction to Artificial Intelligence and Generative AI for Novice
    Author: Neural, Adam
    Published: 2023
    Publisher:  Adam Neural, [Erscheinungsort nicht ermittelbar]

  13. Experimental IR meets multilinguality, multimodality, and interaction
    14th international conference of the CLEF association, CLEF 2023, Thessaloniki, Greece, September 18-21, 2023 : proceedings
    Contributor: Arampatzis, Avi (HerausgeberIn); Kanoulas, Evangelos (HerausgeberIn); Tsikrika, Theodora (HerausgeberIn); Vrochidis, Stefanos (HerausgeberIn); Giachanou, Anastasia (HerausgeberIn); Li, Dan (HerausgeberIn); Aliannejadi, Mohammad (HerausgeberIn); Vlachos, Michalis (HerausgeberIn); Faggioli, Guglielmo (HerausgeberIn); Ferro, Nicola (HerausgeberIn)
    Published: [2023]; © 2023
    Publisher:  Springer, Cham

    This volume LNCS 14163 constitutes the refereed proceedings of 14th International Conference of the CLEF Association, CLEF 2023, in Thessaloniki, Greece, during September 18-21, 2023. The 10 full papers and one short paper included in this book were... more

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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(14163)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    This volume LNCS 14163 constitutes the refereed proceedings of 14th International Conference of the CLEF Association, CLEF 2023, in Thessaloniki, Greece, during September 18-21, 2023. The 10 full papers and one short paper included in this book were carefully reviewed and selected from 35 submissions. The conference focuses on authorship attribution, fake news detection and news tracking, noise-detection in automatically transferred relevance judgments, impact of online education on children's conversational search behavior, analysis of multi-modal social media content, knowledge graphs for sensitivity identification, a fusion of deep learning and logic rules for sentiment analysis, medical concept normalization and domain-specific information extraction. In addition to this, the volume presents 7 "Best of the labs" papers which were reviewed as full paper submissions with the same review criteria. 13 lab overview papers were accepted and represent scientific challenges based on new datasets and real world problems in multimodal and multilingual information access

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Arampatzis, Avi (HerausgeberIn); Kanoulas, Evangelos (HerausgeberIn); Tsikrika, Theodora (HerausgeberIn); Vrochidis, Stefanos (HerausgeberIn); Giachanou, Anastasia (HerausgeberIn); Li, Dan (HerausgeberIn); Aliannejadi, Mohammad (HerausgeberIn); Vlachos, Michalis (HerausgeberIn); Faggioli, Guglielmo (HerausgeberIn); Ferro, Nicola (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031424472
    Corporations / Congresses: International Conference of the CLEF Association, 14. (2023, Thessaloniki)
    Series: Lecture notes in computer science ; 14163
    Subjects: COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Data Processing / Storage & Retrieval; COMPUTERS / Database Management / Data Mining; COMPUTERS / Database Management / General; COMPUTERS / Interactive & Multimedia; Data Mining; Data Warehousing; Data mining; Databases; Datenbanken; Grafische und digitale Media-Anwendungen; Graphical & digital media applications; Information retrieval; Informationsrückgewinnung, Information Retrieval; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: xxi, 534 Seiten, Illustrationen, Diagramme
    Notes:

    Literaturangaben

    Conference Papers.- I nception Models for Fashion Image Captioning: an Extensive Study on Multiple Datasets.- The Best is yet to Come: A Reproducible Analysis of CLEF eHealth TAR Experiments.- Predicting Retrieval Performance Changes in Evolving Evaluation Environments.- Predicting Retrieval Performance Changes in Evolving Evaluation Environments.- Cem Mil Podcasts: A Spoken Portuguese Document Corpus For Multi-modal, Multi-lingual and Multi-Dialect Information Access Research.- Using authorship embeddings to understand writing style in social media.- Trend Detection in Crime-related Time Series with Change Point Detection Methods.- DAVI: a Dataset for Automatic Variant Interpretation.- qCLEF: a Proposal to Evaluate Quantum Annealing for Information Retrieval and Recommender Systems.- Graph-Enriched Biomedical Entity Representation Transformer.- Supervised Machine-Generated Text Detectors: Family and Scale Matters.- Best of CLEF 2022 Labs.- Cross-lingual Candidate Retrieval and Re-ranking for Biomedical Entity Linking.- Humour Translation with Transformers.- Fight Against Misinformation on Social Media: Detecting Attention-Worthy and Harmful Tweets and Verifiable and Check-Worthy Claims.- A Re-labeling Approach based on Approximate Nearest Neighbors for Identifying Gambling Disorders in Social Media.- Touche 2022 Best of Labs: Neural Image Retrieval for Argumentation.- SimpleText Best of Labs in CLEF-2022: Simplify Text Generation with Prompt Engineering.- Answer Retrieval for Math Questions using Structural and Dense Retrieval.- CLEF 2023 Lab Overviews.- Overview of BioASQ 2023: The eleventh BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answering.- Overview of the CLEF-2023 CheckThat! Lab Checkworthiness, Subjectivity, Political Bias, Factuality, and Authority of News Articles and Their Source.- Overview of DocILE 2023: Document Information Localization and Extraction.- Overview of eRisk 2023: Early Risk Prediction on the Internet.- Overview of EXIST 2023 - Learning with Disagreement for Sexism Identification and Characterization.- Intelligent Disease Progression Prediction: Overview of iDPPCLEF 2023.- Overview of the ImageCLEF 2023: Multimedia Retrieval in Medical, Social Media and Internet Applications.- Overview of JOKER - CLEF-2023 Track on Automatic Wordplay Analysis.- Overview of LifeCLEF 2023: evaluation of AI models for the identification and prediction of birds, plants, snakes and fungi.- Overview of the CLEF-2023 LongEval Lab on Longitudinal Evaluation of Model Performance.- Overview of PAN 2023: Authorship Verification, Multi-Author Writing Style Analysis, Profiling Cryptocurrency Influencers, and Trigger Detection.- Overview of the CLEF 2023 SimpleText Lab: Automatic Simplification of Scientific Texts.- Overview of the CLEF 2023 SimpleText Lab: Automatic Simplification of Scientific Texts.
  14. Explainable and transparent AI and multi-agent systems
    5th international workshop, EXTRAAMAS 2023, London, UK, May 29, 2023 : revised selected papers
    Contributor: Calvaresi, Davide (HerausgeberIn); Najjar, Amro (HerausgeberIn); Omicini, Andrea (HerausgeberIn); Aydogan, Reyhan (HerausgeberIn); Carli, Rachele (HerausgeberIn); Ciatto, Giovanni (HerausgeberIn); Mualla, Yazan (HerausgeberIn); Främling, Kary (HerausgeberIn)
    Published: [2023]; © 2023
    Publisher:  Springer, Cham

    This volume LNCS 14127 constitutes the refereed proceedings of the 5th International Workshop, EXTRAAMAS 2023, held in London, UK, in May 2023. The 15 full papers presented together with 1 short paper were carefully reviewed and selected from 26... more

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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(14127)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    This volume LNCS 14127 constitutes the refereed proceedings of the 5th International Workshop, EXTRAAMAS 2023, held in London, UK, in May 2023. The 15 full papers presented together with 1 short paper were carefully reviewed and selected from 26 submissions. The workshop focuses on Explainable Agents and multi-agent systems; Explainable Machine Learning; and Cross-domain applied XAI

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Calvaresi, Davide (HerausgeberIn); Najjar, Amro (HerausgeberIn); Omicini, Andrea (HerausgeberIn); Aydogan, Reyhan (HerausgeberIn); Carli, Rachele (HerausgeberIn); Ciatto, Giovanni (HerausgeberIn); Mualla, Yazan (HerausgeberIn); Främling, Kary (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031408779
    Corporations / Congresses: EXTRAAMAS, 5. (2023, London)
    Series: Array ; 14127
    Subjects: Artificial intelligence; COM094000; COMPUTERS / Artificial Intelligence; COMPUTERS / Compilers; COMPUTERS / Expert Systems; COMPUTERS / Machine Theory; COMPUTERS / Natural Language Processing; Compiler und Übersetzer; Compilers; Expert systems / knowledge-based systems; Künstliche Intelligenz; Machine learning; Maschinelles Lernen; Mathematical theory of computation; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Theoretische Informatik; Wissensbasierte Systeme, Expertensysteme
    Scope: xii, 280 Seiten, Diagramme
    Notes:

    Literaturangaben

    Explainable Agents and multi-agent systems.- Mining and Validating Belief-based Agent Explanations.- Evaluating a mechanism for explaining BDI agent behaviour.- A General-Purpose Protocol for Multi-Agent based Explanations.- Dialogue Explanations for Rules-based AI Systems.- Estimating Causal Responsibility for Explaining Autonomous Behavior.- Explainable Machine Learning.- The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing.- Bottom-Up and Top-Down Workflows for Hypercube- and Clustering-based Knowledge Extractors.- Imperative Action Masking for Safe Exploration in Reinforcement Learning.- Reinforcement Learning in Cyclic Environmental Change for Non-Communicative Agents: A Theoretical Approach.- Inherently Interpretable Deep Reinforcement Learning through Online Mimicking.- Counterfactual, Contrastive, and Hierarchical Explanations with Contextual Importance and Utility.- Cross-domain applied XAI.- Explanation Generation via Decompositional Rules Extraction for Head and Neck Cancer Classification.- Metrics for Evaluating Explainable Recommender Systems.- Leveraging Imperfect Explanations for Plan Recognition Problems.- Reinterpreting Vulnerability to Tackle Deception in Principles-Based XAI for Human-Computer Interaction.- Using Cognitive Models and Wearables to Diagnose and Predict Dementia Patient Behaviour.
  15. Representation Learning for Natural Language Processing
    Contributor: Lin, Yankai (HerausgeberIn); Liu, Zhiyuan (HerausgeberIn); Sun, Maosong (HerausgeberIn)
    Published: 2023
    Publisher:  Springer Verlag, Singapore, Singapore

    This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts.... more

     

    This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing. As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Lin, Yankai (HerausgeberIn); Liu, Zhiyuan (HerausgeberIn); Sun, Maosong (HerausgeberIn)
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9789819915996
    Edition: 2nd ed. 2024
    Subjects: COMPUTERS / Database Management / Data Mining; COMPUTERS / Expert Systems; COMPUTERS / Natural Language Processing; Computational linguistics; Computerlinguistik und Korpuslinguistik; Data Mining; Data mining; Expert systems / knowledge-based systems; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 521 Seiten
    Notes:

    Chapter 1. Representation Learning and NLP.- Chapter 2. Word Representation.- Chapter 3. Compositional Semantics.- Chapter 4. Sentence Representation.- Chapter 5. Document Representation.- Chapter 6. Sememe Knowledge Representation.- Chapter 7. World Knowledge Representation.- Chapter 8. Network Representation.- Chapter 9. Cross-Modal Representation.- Chapter 10. Resources.- Chapter 11. Outlook.
  16. Representation Learning for Natural Language Processing
    Contributor: Lin, Yankai (HerausgeberIn); Liu, Zhiyuan (HerausgeberIn); Sun, Maosong (HerausgeberIn)
    Published: 2023
    Publisher:  Springer Verlag, Singapore, Singapore

    This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts.... more

     

    This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing. As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Lin, Yankai (HerausgeberIn); Liu, Zhiyuan (HerausgeberIn); Sun, Maosong (HerausgeberIn)
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9789819916023
    Edition: 2nd ed. 2024
    Subjects: COMPUTERS / Database Management / Data Mining; COMPUTERS / Expert Systems; COMPUTERS / Natural Language Processing; Computational linguistics; Computerlinguistik und Korpuslinguistik; Data Mining; Data mining; Expert systems / knowledge-based systems; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 521 Seiten
    Notes:

    Chapter 1. Representation Learning and NLP.- Chapter 2. Word Representation.- Chapter 3. Compositional Semantics.- Chapter 4. Sentence Representation.- Chapter 5. Document Representation.- Chapter 6. Sememe Knowledge Representation.- Chapter 7. World Knowledge Representation.- Chapter 8. Network Representation.- Chapter 9. Cross-Modal Representation.- Chapter 10. Resources.- Chapter 11. Outlook.
  17. Generative AI
    How ChatGPT and Other AI Tools Will Revolutionize Business
    Author: Taulli, Tom
    Published: 2023
    Publisher:  Apress, CA

    This book will show how generative technology works and the drivers. It will also look at the applications - showing what various startups and large companies are doing in the space. There will also be a look at the challenges and risk factors. ... more

     

    This book will show how generative technology works and the drivers. It will also look at the applications - showing what various startups and large companies are doing in the space. There will also be a look at the challenges and risk factors. During the past decade, companies have spent billions on AI. But the focus has been on applying the technology to predictions - which is known as analytical AI. It can mean that you receive TikTok videos that you cannot resist. Or analytical AI can fend against spam or fraud or forecast when a package will be delivered. While such things are beneficial, there is much more to AI. The next megatrend will be leveraging the technology to be creative. For example, you could take a book and an AI model will turn it into a movie - at very little cost. This is all part of generative AI. It's still in the nascent stages but it is progressing quickly. Generative AI can already create engaging blog posts, social media messages, beautiful artwork and compelling videos. The potential for this technology is enormous. It will be useful for many categories like sales, marketing, legal, product design, code generation, and even pharmaceutical creation. What You Will Learn The importance of understanding generative AI The fundamentals of the technology, like the foundation and diffusion models How generative AI apps work How generative AI will impact various categories like the law, marketing/sales, gaming, product development, and code generation. The risks, downsides and challenges. Who This Book is For Professionals that do not have a technical background. Rather, the audience will be mostly those in Corporate America (such as managers) as well as people in tech startups, who will need an understanding of generative AI to evaluate the solutions

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9781484293690
    Edition: 1st ed
    Subjects: Algorithms & data structures; Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Expert Systems; COMPUTERS / Information Theory; Computational linguistics; Computerlinguistik und Korpuslinguistik; Datenbanken; Expert systems / knowledge-based systems; Künstliche Intelligenz; LANGUAGE ARTS & DISCIPLINES / Linguistics; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Other subjects: AI Art; DeepMind Gopher; Deepfakes
    Scope: 208 Seiten
    Notes:

    Chapter 1: Introduction to Generative AI.- Chapter 2: Data.- Chapter 3: AI Fundamentals.- Chapter 4: Core Generative AI Technology.- Chapter 5: Large Language Models.- Chapter 6: Auto Code Generation.- Chapter 7: The Transformation of Business.- Chapter 8: The Impact on Major Businesses.- Chapter 9: The Future.
  18. Mammogram Image Classification Using Artificial Intelligence
    Author: M, Velmurugan
    Published: 2023
    Publisher:  Abhilash Book Publishers & Distributors, [Erscheinungsort nicht ermittelbar]

  19. Computational linguistics and intelligent text processing
    20th International Conference, CICLing 2019, La Rochelle, France, April 7-13, 2019, revised selected papers – Part 1
    Contributor: Gelbukh, Alexander (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(13451)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    The two-volume set LNCS 13451 and 13452 constitutes revised selected papers from the CICLing 2019 conference which took place in La Rochelle, France, April 2019.The total of 95 papers presented in the two volumes was carefully reviewed and selected from 335 submissions. The book also contains 3 invited papers.The papers are organized in the following topical sections: General, Information extraction, Information retrieval, Language modeling, Lexical resources, Machine translation, Morphology, sintax, parsing, Name entity recognition, Semantics and text similarity, Sentiment analysis, Speech processing, Text categorization, Text generation, and Text mining

     
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  20. Formal methods
    25th International Symposium, FM 2023, Lubeck, Germany, March 6-10, 2023 : proceedings
    Contributor: Chechik, Marsha (HerausgeberIn); Katoen, Joost-Pieter (HerausgeberIn); Leucker, Martin (HerausgeberIn)
    Published: [2023]
    Publisher:  Springer, Cham

    This book constitutes the refereed proceedings of the 25th International Symposium on Formal Methods, FM 2023, which took place in Lübeck, Germany, in March 2023. The 26 full paper, 2 short papers included in this book were carefully reviewed and... more

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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(1400)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

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    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    This book constitutes the refereed proceedings of the 25th International Symposium on Formal Methods, FM 2023, which took place in Lübeck, Germany, in March 2023. The 26 full paper, 2 short papers included in this book were carefully reviewed and selected rom 95 submissions. They have been organized in topical sections as follows: SAT/SMT; Verification; Quantitative Verification; Concurrency and Memory Models; Formal Methods in AI; Safety and Reliability. The proceedings also contain 3 keynote talks and 7 papers from the industry day

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Chechik, Marsha (HerausgeberIn); Katoen, Joost-Pieter (HerausgeberIn); Leucker, Martin (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031274800
    Corporations / Congresses: International Symposium on Formal Methods, 25. (2023, Lübeck)
    Series: Lecture notes in computer science ; 14000
    Subjects: Algorithms & data structures; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Expert Systems; COMPUTERS / General; COMPUTERS / Hardware / General; COMPUTERS / Programming / General; COMPUTERS / Programming / Software Development; Computer programming / software development; Computerhardware; Computing & information technology; Expert systems / knowledge-based systems; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Programmier- und Skriptsprachen, allgemein; Software Engineering; Software Engineering; Theoretische Informatik; Wissensbasierte Systeme, Expertensysteme
    Scope: xvi, 659 Seiten, Diagramme
    Notes:

    Literaturangaben

    Keynotes.- Symbolic Computation in Automated Program Reasoning.- The next big thing: from embedded systems to embodied actors.- Intelligent and Dependable Decision-Making Under Uncertainty.- A Coq formalization of Lebesgue Induction Principle and Tonelli's Theorem.- SAT/SMT.- Railway Scheduling Using Boolean Satisfiability Modulo Simulations.- SMT Sampling via Model-Guided Approximation.- Efficient SMT-based Network Fault Tolerance Verification.- Verification I.- Formalising the Prevention of Microarchitectural Timing Channels by Operating Systems.- Can we Communicate? Using Dynamic Logic to Verify Team Automata.- The ScalaFix equation solver.- HHLPy: Practical Verification of Hybrid Systems using Hoare Logic.- Quantitative Verification.- symQV: Automated Symbolic Verification of Quantum Programs.- PFL: a Probabilistic Logic for Fault Trees.- Energy Buechi Problems.- QMaude: quantitative specification and verification in rewriting logic.- Concurrency and Memory Models.- Minimisation of Spatial Models using Branching Bisimilarity.- Reasoning about Promises in Weak Memory Models with Event Structures.- A fine-grained semantics for arrays and pointers under weak memory models.- VeyMont: Parallelising Verified Programs instead of Verifying Parallel Programs.- Verification 2.- Verifying At the Level of Java Bytecode.- Abstract Alloy Instances.- Monitoring the Internet Computer.- Word Equations in Synergy with Regular Constraints.- Formal Methods in AI.- Verifying Feedforward Neural Networks for Classification in Isabelle/HOL.- SMPT: A Testbed for Reachabilty Methods in Generalized Petri Nets.- The Octatope Abstract Domain for Verification of Neural Networks.- Program Semantics and Verification Technique for AI-centred Programs.- Safety and Reliability.- Tableaux for Realizability of Safety Specifications.- A Decision Diagram Operation for Reachability.- Formal Modelling of Safety Architecture for Responsibility-AwareAutonomous Vehicle via Event-B Refinement.- A Runtime Environment for Contract Automata.- Industry Day.- Formal and Executable Semantics of the Ethereum Virtual Machine in Dafny.- Shifting Left for Early Detection of Machine-Learning Bugs.- A Systematic Approach to Automotive Security.- Specification-Guided Critical Scenario Identification for Automated Driving.- Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks.- Backdoor Mitigation in Deep Neural Networks via Strategic Retraining.- veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System.
  21. Rules and reasoning
    6th International Joint Conference on Rules and Reasoning, RuleML+RR 2022, Berlin, Germany, September 26-28, 2022 : proceedings
    Contributor: Governatori, Guido (HerausgeberIn); Turhan, Anni-Yasmin (HerausgeberIn)
    Published: [2022]
    Publisher:  Springer, Cham

    This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2022, held in Berlin, Germany, during September 26-28, 2022. This is the 6th conference of a new series, joining the efforts of two existing... more

    Location:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signature:
    RN 2835(13752)
    Inter-library loan:
    No loan of volumes, only paper copies will be sent

    Location:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
    Inter-library loan:
    No inter-library loan

     

    This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2022, held in Berlin, Germany, during September 26-28, 2022. This is the 6th conference of a new series, joining the efforts of two existing conference series, namely "RuleML" (International Web Rule Symposium) and "RR" (Web Reasoning and Rule Systems).The 18 full research papers presented in this book were carefully reviewed and selected from 54 submissions. The papers cover the following topics: answer set programming; foundations of nonmonotonic reasoning; datalog; queries over ontologies; proofs, error-tolerance, and rules; as well as agents and argumentation

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Contributor: Governatori, Guido (HerausgeberIn); Turhan, Anni-Yasmin (HerausgeberIn)
    Language: English
    Media type: Conference proceedings
    Format: Print
    ISBN: 9783031215407
    Corporations / Congresses: International Joint Conference on Rules and Reasoning, 6. (2022, Online)
    Series: Lecture notes in computer science ; 13752
    Subjects: Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Computer Science; COMPUTERS / Data Processing / General; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Database Management / General; COMPUTERS / Expert Systems; Computer science; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Databases; Datenbanken; Expert systems / knowledge-based systems; Künstliche Intelligenz; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Public administration; Theoretische Informatik; Wissensbasierte Systeme, Expertensysteme
    Scope: xii, 304 Seiten
    Notes:

    Interessenniveau: 06, Professional and scholarly: For an expert adult audience, including academic research. (06)

    Answer Set Programming.- Foundations of Nonmonotonic Reasoning.- Datalog.- Queries Over Ontologies.- Proofs, Error-tolerance, and Rules.- Agents and Argumentation.
  22. Foundation Models for Natural Language Processing
    Pre-trained Language Models Integrating Media
    Author: Paaß, Gerhard; Giesselbach, Sven
    Published: 2023
    Publisher:  Springer International Publishing AG, Cham

    This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a... more

     

    This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9783031231896
    Edition: 1st ed. 2023
    Series: Artificial Intelligence: Foundations, Theory, and Algorithms
    Subjects: Artificial intelligence; COM094000; COMPUTERS / Artificial Intelligence; COMPUTERS / Expert Systems; COMPUTERS / Natural Language Processing; Computational linguistics; Computerlinguistik und Korpuslinguistik; Expert systems / knowledge-based systems; Künstliche Intelligenz; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 444 Seiten
    Notes:

    1 Introduction 1.1 Scope of the Book 1.2 Preprocessing of Text 1.3 Vector Space Models and Document Classification 1.4 Nonlinear Classifiers 1.5 Generating Static Word Embeddings 1.6 Recurrent Neural Networks 1.7 Convolutional Neural Networks 1.8 Summary 2 Pre-trained Language Models2.1 BERT: Self-Attention and Contextual Embeddings 2.2 GPT: Autoregressive Language Models 2.3 Transformer: Sequence-to-Sequence Translation 2.4 Training and Assessment of Pre-trained Language Models 3 Improving Pre-trained Language Models 3.2 Capturing Longer Dependencies 3.3 Multilingual Pre-trained Language Models 3.4 Additional Knowledge for Pre-trained Language Models 3.5 Changing Model Size 3.6 Fine-tuning for Specific Applications 4. Knowledge Acquired by Foundation Models 4.1 Benchmark Collections 4.2 Evaluating Knowledge by Probing Classifiers 4.3 Transferability and Reproducibility of Benchmarks 5 Foundation Models for Information Extraction 5.1 Text Classification5.2 Word Sense Disambiguation5.3 Named Entity Recognition 5.4 Relation Extraction 6 Foundation Models for Text Generation 6.1 Document Retrieval6.2 Question Answering 6.3 Neural Machine Translation 6.4 Text Summarization 6.5 Story Generation 6.6 Dialog Systems 7 Foundation Models for Speech, Images, Videos, and Control 7.1 Speech Recognition and Generation7.2 Image Processing and Generation 7.3 Video Interpretation and Generation 7.4 Controlling Dynamic Systems 8 Summary and Outlook 8.1 Foundation Models are a New Paradigm 8.2 Potential Harm from Foundation Models 8.3 Advanced Artificial Intelligence Systems Appendix
  23. Foundation Models for Natural Language Processing
    Pre-trained Language Models Integrating Media
    Author: Paaß, Gerhard; Giesselbach, Sven
    Published: 2023
    Publisher:  Springer International Publishing AG, Cham

    This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a... more

     

    This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI

     
    Export to reference management software   RIS file
      BibTeX file
    Content information
    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9783031231926
    Edition: 1st ed. 2023
    Series: Artificial Intelligence: Foundations, Theory, and Algorithms
    Subjects: Artificial intelligence; COM094000; COMPUTERS / Artificial Intelligence; COMPUTERS / Expert Systems; COMPUTERS / Natural Language Processing; Computational linguistics; Computerlinguistik und Korpuslinguistik; Expert systems / knowledge-based systems; Künstliche Intelligenz; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 444 Seiten
    Notes:

    1 Introduction 1.1 Scope of the Book 1.2 Preprocessing of Text 1.3 Vector Space Models and Document Classification 1.4 Nonlinear Classifiers 1.5 Generating Static Word Embeddings 1.6 Recurrent Neural Networks 1.7 Convolutional Neural Networks 1.8 Summary 2 Pre-trained Language Models2.1 BERT: Self-Attention and Contextual Embeddings 2.2 GPT: Autoregressive Language Models 2.3 Transformer: Sequence-to-Sequence Translation 2.4 Training and Assessment of Pre-trained Language Models 3 Improving Pre-trained Language Models 3.2 Capturing Longer Dependencies 3.3 Multilingual Pre-trained Language Models 3.4 Additional Knowledge for Pre-trained Language Models 3.5 Changing Model Size 3.6 Fine-tuning for Specific Applications 4. Knowledge Acquired by Foundation Models 4.1 Benchmark Collections 4.2 Evaluating Knowledge by Probing Classifiers 4.3 Transferability and Reproducibility of Benchmarks 5 Foundation Models for Information Extraction 5.1 Text Classification5.2 Word Sense Disambiguation5.3 Named Entity Recognition 5.4 Relation Extraction 6 Foundation Models for Text Generation 6.1 Document Retrieval6.2 Question Answering 6.3 Neural Machine Translation 6.4 Text Summarization 6.5 Story Generation 6.6 Dialog Systems 7 Foundation Models for Speech, Images, Videos, and Control 7.1 Speech Recognition and Generation7.2 Image Processing and Generation 7.3 Video Interpretation and Generation 7.4 Controlling Dynamic Systems 8 Summary and Outlook 8.1 Foundation Models are a New Paradigm 8.2 Potential Harm from Foundation Models 8.3 Advanced Artificial Intelligence Systems Appendix
  24. KI-Innovationen
    Wie die Technologie die Grenzen verschiebt Künstliche Intelligenz verstehen und nutzen: Ein AI-Buch
    Author: Dujardin, Jhon
    Published: 2023
    Publisher:  Thaipan Legal, [Erscheinungsort nicht ermittelbar]

  25. Question Answering over Text and Knowledge Base
    Author: Momtazi, Saeedeh; Abbasiantaeb, Zahra
    Published: 2023
    Publisher:  Springer International Publishing AG, Cham

    This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the... more

     

    This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning. After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9. This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge

     
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    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9783031165542
    Edition: 1st ed. 2022
    Subjects: COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Data Processing / Storage & Retrieval; COMPUTERS / Expert Systems; Data Warehousing; Expert systems / knowledge-based systems; Information retrieval; Informationsrückgewinnung, Information Retrieval; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Wissensbasierte Systeme, Expertensysteme
    Scope: 202 Seiten
    Notes:

    - 1. Introduction. - 2. History and Architecture. - 3. Question Answering Evaluation. - 4. Introduction to Neural Networks. - 5. Question Answering over Text. - 6. Question Answering over Knowledge Base. - 7. KBQA Enhanced with Textual Data. - 8. Question Answering in Real Applications. - 9. Future Directions of Question Answering.