Efficient query evaluation using a two-level retrieval process
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
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We describe a fast query evaluation method for ad document retrieval in online advertising, based upon the classic WAND algorithm. The key idea is to localize per-topic term upper bounds into homogeneous ad groups. Our approach is not only theoretically motivated by a topical mixture model; but empirically justified by the characteristics of the ad domain, that is, short and semantically focused documents with natural hierarchy. We report experimental results using artificial and real-world query-ad retrieval data, and show that the tighter-bound WAND outperforms the traditional approach by 35.4% reduction in number of full evaluations.