Methods for information server selection

Abstract

The problem of using a broker to select a subset of available information servers in order to achieve a good trade-off between document retrieval effectiveness and cost is addressed. Server selection methods which are capable of operating in the absence of global information, and where servers have no knowledge of brokers, are investigated. A novel method using Lightweight Probe queries (LWP method) is compared with several methods based on data from past query processing, while Random and Optimal server rankings serve as controls. Methods are evaluated, using TREC data and relevance judgments, by computing ratios, both empirical and ideal, of recall and early precision for the subset versus the complete set of available servers. Estimates are also made of the best-possible performance of each of the methods. LWP and Topic Similarity methods achieved best results, each being capable of retrieving about 60% of the relevant documents for only one-third of the cost of querying all servers. Subject to the applicable cost model, the LWP method is likely to be preferred because it is suited to dynamic environments. The good results obtained with a simple automatic LWP implementation were replicated using different data and a larger set of query topics.