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Hybrid Intelligent Systems for Information Retrieval [Pehme köide]

(Persistent University, Pune), , (PC College of Eng., Pune, India)
  • Formaat: Paperback / softback, 234 pages, kõrgus x laius: 234x156 mm, kaal: 400 g, 15 Tables, black and white; 69 Line drawings, black and white; 3 Halftones, black and white; 72 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Computational Intelligence and Its Applications
  • Ilmumisaeg: 08-Oct-2024
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1032035706
  • ISBN-13: 9781032035703
  • Formaat: Paperback / softback, 234 pages, kõrgus x laius: 234x156 mm, kaal: 400 g, 15 Tables, black and white; 69 Line drawings, black and white; 3 Halftones, black and white; 72 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Computational Intelligence and Its Applications
  • Ilmumisaeg: 08-Oct-2024
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1032035706
  • ISBN-13: 9781032035703

The book covers three areas along with the introduction to Intelligent IR, i.e. Optimal Information Retrieval using Evolutionary approaches, Semantic Search for Web Information Retrieval and Natural Language Processing for Information Retrieval.



Hybrid Intelligent Systems for Information Retrieval covers three areas along with the introduction to Intelligent IR, i.e., Optimal Information Retrieval Using Evolutionary Approaches, Semantic Search for Web Information Retrieval, and Natural Language Processing for Information Retrieval.

• Talks about the design, implementation, and performance issues of the hybrid intelligent information retrieval system in one book

• Gives a clear insight into challenges and issues in designing a hybrid information retrieval system

• Includes case studies on structured and unstructured data for hybrid intelligent information retrieval

• Provides research directions for the design and development of intelligent search engines

This book is aimed primarily at graduates and researchers in the information retrieval domain.

1. Introduction.
2. Matching Functions.
3. Information Retrieval Models.
4. Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval.
5.
Information Retrieval and Semantic Search.
6. Ontology Creation using
Clustering Technique.
7. Natural Language Processing for Information
Retrieval.
8. Deep learning (DL) for Information retrieval (IR).
9.
Application of Ontology in Domain Specific Information Retrieval: A case
study.
10. Applications of Natural Language Processing and Information
Retrieval.