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Rajashekar, T.B.; Croft, W.B.: Combining automatic and manual index representations in probabilistic retrieval (1995) 0.00
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Abstract

Results from research in information retrieval have suggested that significant improvements in retrieval effectiveness can be obtained by combining results from multiple index representioms, query formulations, and search strategies. The inference net model of retrieval, which was designed from this point of view, treats information retrieval as an evidental reasoning process where multiple sources of evidence about document and query content are combined to estimate relevance probabilities. Uses a system based on this model to study the retrieval effectiveness benefits of combining these types of document and query information that are found in typical commercial databases and information services. The results indicate that substantial real benefits are possible
Croft, W.B.; Harper, D.J.: Using probabilistic models of document retrieval without relevance information (1979) 0.00
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Abstract

Based on a probablistic model, proposes strategies for the initial search and an intermediate search. Retrieval experiences with the Cranfield collection of 1,400 documents show that this initial search strategy is better than conventional search strategies both in terms of retrieval effectiveness and in terms of the number of queries that retrieve relevant documents. The intermediate search is a useful substitute for a relevance feedback search. A cluster search would be an effective alternative strategy.

Search (2 results, page 1 of 1)

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