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A Methodology for Collection Selection in Heterogeneous Contexts

Abstract : In this paper we demonstrate that in an ideal Distributed Information Retrieval environment, taking the ability of each collection server to return relevant documents into account when selecting collections can be effective. Based on this assumption, we suggest a new approach to resolve the collection selection problem. In order to predict a collection's ability to return relevant documents, we inspect a limited number n of documents retrieved from each collection and analyze the proximity of search keywords within them. In our experiments, we vary the underlying parameter n of our suggested model to define the most appropriate number of top documents to be inspected. Moreover, we evaluate the retrieval effectiveness of our approach and compare it with both the centralized indexing and the CORI approaches [1], [16]. Preliminary results from these experiments, conducted on WT10g test collection, tend to demonstrate that our suggested method can achieve appreciable retrieval effectiveness.
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https://hal-emse.ccsd.cnrs.fr/emse-00948054
Contributor : Florent Breuil <>
Submitted on : Monday, February 17, 2014 - 4:29:37 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:08 PM

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  • HAL Id : emse-00948054, version 1

Citation

Faïza Abbaci, Jacques Savoy, Michel Beigbeder. A Methodology for Collection Selection in Heterogeneous Contexts. ITCC2002, International Conference on Information Technology: Coding and Computing, Apr 2002, Las Vegas, United States. 7p. ⟨emse-00948054⟩

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