Proceedings of the 15th international conference on World Wide Web
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
Proceedings of the 17th ACM conference on Information and knowledge management
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Effective search session segmentation "grouping queries according to common task or intent" can be useful for improving relevance, search evaluation, and query suggestion. Previous work has largely attempted to segment search sessions off-line, after the fact. In contrast, we present preliminary investigation of predicting, in real time, whether a user is about to switch interest - that is, whether the user is about to finish the current search and switch to another search task (or stop searching altogether). We explore an approach for this task using client-side user behavior such as clicks, scrolls, and mouse movements, contextualized by the content of the search result pages and previous searches. Our experiments over thousands of real searches show that we can identify context and user behavior patterns that indicate that a user is about to switch to a new search task. These preliminary results can be helpful for more effective query suggestion and personalization.