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

BibTeX entry

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.

BibTeX entry

Fulltext as PDF