Evaluating different methods of estimating retrieval quality for resource selection

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In a federated digital library system, it is too expensive to query every accessible library. Resource selection is the task to decide to which libraries a query should be routed. Most existing resource selection algorithms compute a library ranking in a heuristic way. In contrast, the decision-theoretic framework (DTF) follows a different approach on a better theoretic foundation: It computes a selection which minimises the overall costs (e.g. retrieval quality, time, money) of the distributed retrieval. For estimating retrieval quality the recall-precision function is proposed. In this paper, we introduce two new methods: The first one computes the empirical distribution of the probabilities of relevance from a small library sample, and assumes it to be representative for the whole library. The second method assumes that the indexing weights follow a normal distribution, leading to a normal distribution for the document scores. Furthermore, we present the first evaluation of DTF by comparing this theoretical approach with the heuristical stateof- the-art system CORI; here we find that DTF outperforms CORI in most cases.
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Dokumententyp:
Wissenschaftliche Texte » Artikel, Aufsatz
Fakultät / Institut:
Fakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft
Dewey Dezimal-Klassifikation:
000 Informatik, Informationswissenschaft, allgemeine Werke » 000 Informatik, Wissen, Systeme » 004 Datenverarbeitung; Informatik
Stichwörter:
normal distribution, desicion-theoretic framework, formal models, Resource selection
Sprache:
Englisch
Kollektion / Status:
E-Publikationen / Dokument veröffentlicht
Dokument erstellt am:
01.07.2003
Dateien geändert am:
01.08.2013
Medientyp:
Text
Quelle:
SIGIR 2003 : proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28 to August 1, 2003, Toronto, Canada / edited by Jamie Callan ... - New York, 2003