Mining for insights in the search engine query stream.

Search engines record a large amount of metadata each time a user issues a query. While efficiently mining this data can be challeng-ing, the results can be useful in multiple ways, including monitoring search engine performance, improving search relevance, prioritizing research, and optimizing day-to-day operations. In this poster, we describe an approach for mining query log data for actionable insights - specific query segments (sets of queries) that require attention, and actions that need to be taken to improve the segments. Starting with a set of important metrics, we identify query segments that are "interesting" with respect to these metrics using a distributed frequent itemset mining algorithm.