Evaluating the Cost of Boolean Query Mapping

15 years 11 months ago

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Non-uniform query languages make searching over heterogeneous information sources difﬁcult. 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 ﬁlter query to yield the correct ﬁnal results. This post-ﬁltering approach may involve signiﬁcant cost because the documents that the users will not see may have to be retrieved and ﬁltered. There are generally two ways to implement post-ﬁltering: batch post-ﬁltering and incremental post-ﬁltering. 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-ﬁltering cost may be acceptable, while the batch post-ﬁltering cost may sometimes be extremely large.

Kevin Chen-Chuan Chang, Hector Garcia-Molina

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