OLAP on search logs: an infrastructure supporting data-driven applications in search engines

Authors:
Bin Zhou;Daxin Jiang;Jian Pei;Hang Li
Affiliations:
Simon Fraser University, Burnaby, BC, Canada;Microsoft Research Asia, Beijing, China;Simon Fraser University, Burnaby, BC, Canada;Microsoft Research Asia, Beijing, China
Venue:
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2009

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Abstract

Search logs, which contain rich and up-to-date information about users' needs and preferences, have become a critical data source for search engines. Recently, more and more data-driven applications are being developed in search engines based on search logs, such as query suggestion, keyword bidding, and dissatisfactory query analysis. In this paper, by observing that many data-driven applications in search engines highly rely on online mining of search logs, we develop an OLAP system on search logs which serves as an infrastructure supporting various data-driven applications. An empirical study using real data of over two billion query sessions demonstrates the usefulness and feasibility of our design.