Journal article

Boosting search performance using query variations

R Benham, Joel Mackenzie, A Moffat, JS Culpepper

ACM Transactions on Information Systems | Association for Computing Machinery | Published : 2019

Abstract

Rank fusion is a powerful technique that allows multiple sources of information to be combined into a single result set. Query variations covering the same information need represent one way in which different sources of information might arise. However, when implemented in the obvious manner, fusion over query variations is not cost-effective, at odds with the usual web-search requirement for strict per-query efficiency guarantees. In this work, we propose a novel solution to query fusion by splitting the computation into two parts: One phase that is carried out offline, to generate pre-computed centroid answers for queries addressing broadly similar information needs, and then a second onl..

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Grants

Awarded by Australian Research Council


Funding Acknowledgements

The first author was supported by an RMIT Vice Chancellors PhD Scholarship. The second author was supported by an Australian Research Training Program Scholarship. The fourth author was supported by the Australian Research Council’s Discovery Projects Scheme (DP170102231), a Google Faculty Research Award, and an Amazon Research Award.