Evaluating different methods of estimating retrieval quality for resource selection
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- Citation-Key:
- Nottelmann/Fuhr:03a
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- Title:
- Evaluating different methods of estimating retrieval quality for resource selection
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- Author(s):
- H. Nottelmann
- N. Fuhr
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- In:
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- Citation-Key:
- SIGIR:03
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- Title:
- Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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- Editor(s):
- Jamie Callan
- Gordon Cormack
- Charles Clarke
- David Hawking
- Alan Smeaton
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- Publisher:
- ACM
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- In:
- Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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- Year:
- 2003
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- Year:
- 2003
Abstract:
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 state-of-the-art system CORI; here we find that DTF outperforms CORI in most cases.
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