DISTRIBUTED INFORMATION RETRIEVAL: A MULTI-OBJECTIVE RESOURCE SELECTION APPROACH
Shengli Wu, Fábio Crestani · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 2003
Information retrieval is becoming increasingly concerned with resource selection and data fusion for distributed archives. In distributed information retrieval, a user submits a query to a broker, which determines a solution for how to yield a given number of documents from all available resources. In this paper, we present a multi-objective model for resource selection, in which four aspects: a document's relevance to the given query, time, monetary cost, and the chance of getting document duplicates from resources, are considered simultaneously. Some variants of this multi-objective model, aimed at achieving better implementation efficiency, are also proposed.