Information retrieval and natural language processing : a graph theory approach

著者

    • Sonawane, Sheetal S.
    • Mahalle, Parikshit N.
    • Ghotkar, Archana S.

書誌事項

Information retrieval and natural language processing : a graph theory approach

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

（Studies in big data, v. 104）

Springer, c2022

  • : [hardback]

大学図書館所蔵 件 / 全2件

この図書・雑誌をさがす

注記

Includes bibliographical references

内容説明・目次

内容説明

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.

目次

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.

「Nielsen BookData」 より

関連文献： 1件中  1-1を表示

詳細情報

ページトップへ