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Proceedings Paper

Retrieval scheme for cluster-based adaptive information retrieval based on term refinement
Author(s): Jay N. Bhuyan; Jitender S. Deogun; Vijay V. Raghavan
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Paper Abstract

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.

Paper Details

Date Published: 23 March 1993
PDF: 13 pages
Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); doi: 10.1117/12.141748
Show Author Affiliations
Jay N. Bhuyan, Tuskegee Univ. (United States)
Jitender S. Deogun, Univ. of Nebraska/Lincoln (United States)
Vijay V. Raghavan, Univ. of Southwestern Louisiana (United States)


Published in SPIE Proceedings Vol. 1963:
Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry
Usama M. Fayyad; Ramasamy Uthurusamy, Editor(s)

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