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Savoy, Jacques

Nom
Savoy, Jacques
Affiliation principale
Fonction
Professeur.e ordinaire
Email
jacques.savoy@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/282
_
0000-0002-4486-0067

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  • Publication
    Métadonnées seulement
    Result merging strategies for a current news metasearcher
    (2003)
    Rasolofo, Yves
    ;
    Hawking, David
    ;
    Savoy, Jacques 
    Metasearching of online current news services is a potentially useful Web application of distributed information retrieval techniques. We constructed a realistic current news test collection using the results obtained from 15 current news Web sites (including ABC News, BBC and AllAfrica) in response to 107 topical queries. Results were judged for relevance by independent assessors. Online news services varied considerably both in the usefulness of the results sets they returned and also in the amount of information they provided which could be exploited by a metasearcher. Using the current news test collection we compared a range of different merging methods. We found that a low-cost merging scheme based on a combination of available evidence (title, summary, rank and server usefulness) worked almost as well as merging based on downloading and rescoring the actual news articles. (C) 2002 Elsevier Science Ltd. All rights reserved.
  • Publication
    Accès libre
    Approaches to Collection Selection and Results Merging for Distributed Information Retrieval
    (2001)
    Rasolofo, Yves
    ;
    Abbaci, Faïza
    ;
    Savoy, Jacques 
    We have investigated two major issues in Distributed Information Retrieval (DIR), namely: collection selection and search results merging. While most published works on these two issues are based on pre-stored metadata, the approaches described in this paper involve extracting the required information at the time the query isprocessed. In order to predict the relevance of collections to a given query, we analyse a limited number of full documents (e.g., the top five documents) retrieved from each collection and then consider term proximity within them. On the other hand, our merging technique is rather simple since input only requires document scores and lengths of results lists. Our experiments evaluate the retrieval effectiveness of these approaches and compare them with centralised indexing and various other DIR techniques (e.g., CORI [2][3][23]).
    We conducted our experiments using two testbeds: one containing news articles extracted from four different sources (2 GB) and another containing 10 GB of Web pages. Our evaluations demonstrate that the retrieval effectiveness of our simple approaches is worth considering.