Evaluating the Cost of Boolean Query Mapping

Abstract

Non-uniform query languages make searching over heterogeneous information sources difcult. Our approach is to allow a user to compose Boolean queries in one rich front-end language. For each user query and target source, we transform the user query into a subsuming query that can be supported by the source but that may return extra documents. The results are then processed by a lter query to yield the correct nal results. This post-ltering approach may involve signicant cost because the documents that the users will not see may have to be retrieved and ltered. There are generally two ways to implement post-ltering: batch post-ltering and incremental post-ltering. In this paper we evaluate the costs of both methods for different search features such as proximity operators. The experimental results show that in many cases incremental post-ltering cost may be acceptable, while the batch post-ltering cost may sometimes be extremely large.