Ranking Documents in Thesaurus-Based Boolean Retrieval Systems

Abstract In this paper we investigate document ranking methods in thesaurus-based boolean retrieval systems, and propose a new thesaurus-based ranking algorithm called the Extended Relevance (E-Relevance) algorithm. The E-Relevance algorithm integrates the extended boolean model and the thesaurus-based relevance algorithm. Since the E-Relevance algorithm has all the desirable properties of the extended boolean model, it avoids the various problems of previous thesaurus-based ranking algorithms. The E-Relevance algorithm also ranks documents effectively by using term dependence information from the thesaurus. We have shown through performance comparison that the proposed algorithm achieves higher retrieval effectiveness than the others proposed earlier.

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