English, Article edition: Optimising the Heuristics in Latent Semantic Indexing for Effective Information Retrieval S. Srinivas; Ch. AswaniKumar

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Physical Description
  • article
Language
  • English

Edition details

Title
  • Optimising the Heuristics in Latent Semantic Indexing for Effective Information Retrieval
Author
  • S. Srinivas
  • Ch. AswaniKumar
Physical Description
  • article
Notes
  • Latent Semantic Indexing (LSI) is a famous Information Retrieval (IR) technique that tries to overcome the problems of lexical matching using conceptual indexing. LSI is a variant of vector space model and proved to be 30% more effective. Many studies have reported that good retrieval performance is related to the use of various retrieval heuristics. In this paper, we focus on optimising two LSI retrieval heuristics: term weighting and rank approximation. The results obtained demonstrate that the LSI performance improves significantly with the combination of optimised term weighting and rank approximation.
  • Information retrieval, Latent Semantic Indexing, rank approximation, term weighting, vector space method
  • RePEc:wsi:jikmxx:v:05:y:2006:i:02:p:97-105
Language
  • English
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