Information retrieval and natural language processing : a graph theory approach / Sheetal S. Sonawane, Parikshit N. Mahalle, Archana S. Ghotkar.
Sonawane, Sheetal S.; Mahalle, Parikshit N.; Ghotkar, Archana S.
2022
ZA3075
Available Online

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Title Information retrieval and natural language processing : a graph theory approach / Sheetal S. Sonawane, Parikshit N. Mahalle, Archana S. Ghotkar.
Author Sonawane, Sheetal S.
ISBN 9789811699955 (electronic bk.)
981169995X (electronic bk.)
9811699941
9789811699948
DOI https://doi.org/10.1007/978-981-16-9995-5
Imprint Singapore : Springer, 2022.
Language English
Description 1 online resource (186 pages)
Other Standard Identifiers 10.1007/978-981-16-9995-5 doi
Call Number ZA3075
Dewey Decimal Classification 025.04
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed March 8, 2022).
Added Author Mahalle, Parikshit N.
Ghotkar, Archana S.
Series Studies in big data ; v. 104.
Available in Other Form Information Retrieval and Natural Language Processing.
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Record Appears in Online Resources > Ebooks
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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.

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