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Hybrid Intelligent Systems for Information Retrieval: Chapman & Hall/CRC Computational Intelligence and Its Applications

Autor Anuradha D Thakare, Shilpa Laddha, Ambika Pawar
en Limba Engleză Paperback – 8 oct 2024
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.
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Specificații

ISBN-13: 9781032035703
ISBN-10: 1032035706
Pagini: 252
Ilustrații: 144
Dimensiuni: 156 x 234 mm
Greutate: 0.47 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Computational Intelligence and Its Applications

Locul publicării:Boca Raton, United States

Public țintă

Academic, Postgraduate, Professional, and Undergraduate Advanced

Cuprins

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.

Descriere

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.