People often repeat Web searches, both to find new information on topics they have previously explored and to re-find information they have seen in the past. The query associated with a repeat search may differ from the initial query but can nonetheless lead to clicks on the same results. This paper explores repeat search behavior through the analysis of a one-year Web query log of 114 anonymous users and a separate controlled survey of an additional 119 volunteers. Our study demonstrates that as many as 40 % of all queries are re-finding queries. Refinding appears to be an important behavior for search engines to explicitly support, and we explore how this can be done. We demonstrate that changes to search engine results can hinder refinding, and provide a way to automatically detect repeat searches and predict repeat clicks.

Re-finding, a common Web task, is difficult when previously viewed information is modified, moved, or removed. For example, if a person finds a good result using the query “breast cancer treatments”, she expects to be able to use the same query to locate the same result again. While re-finding could be supported by caching the original list, caching precludes the discovery of new information, such as, in this case, new treatment options. People often use search engines to simultaneously find and re-find information. The Re:Search Engine is designed to support both behaviors in dynamic environments like the Web by preserving only the memorable aspects of a result list. A study of result list memory shows that people forget a lot. The Re:Search Engine takes advantage of these memory lapses to include new results where old results have been forgotten.

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