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Term Proximity Scoring for Keyword-Based Retrieval Systems
Auteur(s)
Rasolofo, Yves
Editeur(s)
Date de parution
2003
In
Lecture Notes in Computer Science (LNCS), Springer, 2003/2633//1611-3349
Résumé
This paper suggests the use of proximity measurement in combination with the Okapi probabilistic model. First, using the Okapi system, our investigation was carried out in a distributed retrieval framework to calculate the same relevance score as that achieved by a single centralized index. Second, by applying a term-proximity scoring heuristic to the top documents returned by a keyword-based system, our aim is to enhance retrieval performance. Our experiments were conducted using the TREC8, TREC9 and TREC10 test collections, and show that the suggested approach is stable and generally tends to improve retrieval effectiveness especially at the top documents retrieved.
Autre version
http://dx.doi.org/10.1007/3-540-36618-0_15
Type de publication
Resource Types::text::journal::journal article
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