Abstract
Large search engines process thousands of queries per second over billions of documents, making a huge performance gap between disjunctive and conjunctive queries. An important class of optimization techniques called top-k processing is therefore used to narrow the gap. In this paper, we propose an aggressive algorithm based on the document-at-a-time (DAAT) MaxScore, aiming at further reducing the query latency of disjunctive queries. Essentially, our approach, named Aggressive MaxScore (AMaxScore), can speed up quickly by fine-tuning the initial top-k threshold, which allows a first aggressive process and then a supplementary process if not enough results are returned. Experiments with TREC GOV2 collection show that our approach reduces disjunctive query processing time by almost 15.4% on average over the state-of-the-art MaxScore baseline, while still returns the same results as the disjunctive evaluation.
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Jiang, K., Song, X., Yang, Y. (2014). Faster MaxScore Document Retrieval with Aggressive Processing. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_1
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DOI: https://doi.org/10.1007/978-3-319-08010-9_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08009-3
Online ISBN: 978-3-319-08010-9
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