Can I read Information Retrieval and Natural Language Processing: A Graph Theory Approach (Studies in Big Data, 104) on EtoBox?

Information Retrieval and Natural Language Processing: A Graph Theory Approach (Studies in Big Data, 104) by Sheetal S. Sonawane; Parikshit N. Mahalle; Archana S. Ghotkar is a nonfiction available to read on EtoBox.

What is Information Retrieval and Natural Language Processing: A Graph Theory Approach (Studies in Big Data, 104) about?

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.

Who reads Information Retrieval and Natural Language Processing: A Graph Theory Approach (Studies in Big Data, 104)?

Author

Sheetal S. Sonawane; Parikshit N. Mahalle; Archana S. Ghotkar

Publisher

Springer Singapore : Imprint: Springer

Published

2022

Language

EN

ISBN

9789811699955

Category

nonfiction

Subjects

Mathematics, Management, Computer Science