A retrieval scheme for cluster-based adaptive Information retrieval based on term refinement

Jay N. Bhuyan, Jitender S. Deogun, Vijay V. Raghavan

Research output: Contribution to journalConference articlepeer-review


This paper discusses a retrieval scheme for an Information Retrieval system in which the feedback from a number of users of the system about its performance (global feedback) is stored in the form of clusters called user-oriented clusters. The clusters are described by using the description of its constituent documents. The clusters and queries are represented as vectors and the measure of similarity between them is represented as the cosine of the angle between the two. The clusters are retrieved as per decreasing order of similarity with respect to a query. An important problem that arises in the context of cluster description is the significance of an index term assigned to documents. This problem, called term refinement problem, is formulated and solved. The experimental results of the proposed retrieval scheme are compared with those of the vector space model and the results obtained are encouraging.

Original languageEnglish (US)
Pages (from-to)303-315
Number of pages13
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Mar 23 1993
EventApplications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry - Orlando, United States
Duration: Apr 11 1993Apr 16 1993

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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