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  1. Information Retrieval and Natural Language Processing
    A Graph Theory Approach
    Author: Sonawane, Sheetal S.; Ghotkar, Archana S.; Mahalle, Parikshit N.
    Published: 2023
    Publisher:  Springer Verlag, Singapore, Singapore

    This book gives a comprehensive view of graph theory in informational retrieval (IR) and natural language processing(NLP). This book provides number of graph techniques for IR and NLP applications with examples. It also provides understanding of... more

     

    This book gives a comprehensive view of graph theory in informational retrieval (IR) and natural language processing(NLP). This book provides number of graph techniques for IR and NLP applications with examples. It also provides understanding of graph theory basics, graph algorithms and networks using graph. The book is divided into three parts and contains nine chapters. The first part gives graph theory basics and graph networks, and the second part provides basics of IR with graph-based information retrieval. The third part covers IR and NLP recent and emerging applications with case studies using graph theory.This book is unique in its way as it provides a strong foundation to a beginner in applying mathematical structure graph for IR and NLP applications. All technical details that include tools and technologies used for graph algorithms and implementation in Information Retrieval and Natural Language Processing with its future scope are explained in a clear and organized format

     
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    Content information
    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9789811699979
    Edition: 1st ed. 2022
    Series: Studies in Big Data
    Subjects: Algorithms & data structures; Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Information Theory; COMPUTERS / Security / General; Combinatorics & graph theory; Computer security; Computersicherheit; Datenbanken; Kombinatorik und Graphentheorie; MATHEMATICS / Graphic Methods; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Netzwerksicherheit
    Scope: 176 Seiten
    Notes:

    Part A.- Chapter 1. Graph theory basics.- Chapter 2. Graph Algorithms.- Chapter 3. Networks using graph.- Part B.- Chapter 4. Information retrieval.- Chapter 5. Text document preprocessing using graph theory.- Chapter 6. Text analytics using graph theory.- Chapter 7. Knowledge graph.- Part C.- Chapter 8. Emerging Applications and development.- Chapter 9. Conclusion and future scope.