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Hybrid Intelligent Systems for Information Retrieval

Anuradha D Thakare | Shilpa Laddha | Ambika Pawar
€173.60
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A01=Ambika Pawar
A01=Anuradha D Thakare
A01=Shilpa Laddha
academic research guide
Author_Ambika Pawar
Author_Anuradha D Thakare
Author_Shilpa Laddha
Category=UNH
Category=UYQL
Category=UYQM
Cluster Elements
Cluster Head
deep learning applications
End Procedure
eq_bestseller
eq_computing
eq_isMigrated=1
eq_nobargain
eq_non-fiction
evolutionary computation
Generated Weight Matrix
intelligent search engine design
IR
IR System
IR Technique
Matching Coefficients
Matching Functions
NLP Technique
Ontological Token
ontology-based retrieval
Part Of Speech Tagging
PSO Algorithm
Reset Gate
Scout Bees
Semantic IR
Semantic SE
Semantic Search
Stop Word Removal
structured data analysis
swarm intelligence methods
Template Token
Traditional Search Engines
UCI Repository
User Query
Word Embeddings
Word Tokenization

Product details

  • ISBN 9781032035680
  • Weight: 630g
  • Dimensions: 156 x 234mm
  • Publication Date: 22 Nov 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Description

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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