@inproceedings{Nottelmann/Fuhr:03a,
  author={H. Nottelmann and N. Fuhr},
  title={Evaluating different methods of estimating retrieval quality for resource selection},
  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.},
  crossref={SIGIR:03},
  entrydate=20030401,
  key={Nottelmann/Fuhr:03a},
  year=2003,
}