Conference Proceedings

Accelerated query processing via similarity score prediction

M Petri, A Moffat, J Mackenzie, J Shane Culpepper, D Beck

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval | ACM | Published : 2019

Abstract

Publication rights licensed to ACM. Processing top-k bag-of-words queries is critical to many information retrieval applications, including web-scale search. In this work, we consider algorithmic properties associated with dynamic pruning mechanisms. Such algorithms maintain a score threshold (the k th highest similarity score identified so far) so that low-scoring documents can be bypassed, allowing fast top-k retrieval with no loss in effectiveness. In standard pruning algorithms the score threshold is initialized to the lowest possible value. To accelerate processing, we make use of term- and query-dependent features to predict the final value of that threshold, and then employ the predic..

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Grants

Awarded by Australian Research Council


Funding Acknowledgements

The third author was supported by an Australian Research Training Program Scholarship. The fifth author was suppported by the Australian Research Council (DP160102686).