Information retrieval and natural language processing : a graph theory approach
Author(s)
Bibliographic Information
Information retrieval and natural language processing : a graph theory approach
（Studies in big data, v. 104）
Springer, c2022
- : [hardback]
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Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"