Information Retrieval and Natural Language Processing - A Graph Theory Approach (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Studies in Big Data, 104
Release date:	February 2022
First published:	2022
Authors:	Sheetal S. Sonawane • Parikshit N. Mahalle • Archana S. Ghotkar
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	176
Edition:	1st ed. 2022
ISBN-13:	978-981-16-9994-8
Categories:	Books > Science & Mathematics > Mathematics > Combinatorics & graph theory Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Computer communications & networking > Network security Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
LSN:	981-16-9994-1
Barcode:	9789811699948

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