Information Retrieval and Natural Language Processing

Information Retrieval and Natural Language Processing A Graph Theory Approach - Studies in Big Data

Hardback (23 Feb 2022)

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Publisher's Synopsis

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.


Book information

ISBN: 9789811699948
Publisher: Springer Nature Singapore
Imprint: Springer
Pub date:
DEWEY: 006.35
DEWEY edition: 23
Language: English
Number of pages: 176
Weight: 454g
Height: 235mm
Width: 155mm
Spine width: 13mm