Personalizing Atypical Web Search Sessions

Most research in Web search personalization models users as static or slowly evolving entities with a given set of preferences defined by their past behavior. However, recent publications as well as empirical evidence suggest that for a significant number of search sessions, users diverge from their regular search profiles in order to satisfy atypical, limited duration information needs. In this work, we conduct a large-scale inspection of real-life search sessions to further understand this scenario. Subsequently, we design an automatic means of detecting and supporting such atypical sessions. We demonstrate significant improvements over state-of-the-art Web search personalization techniques by accounting for the typicality of search sessions. The proposed method is evaluated based on Web-scale search session data spanning several months of user activity.

In  Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM '13).

Publisher  ACM

Details

TypeInproceedings
URLhttp://research.microsoft.com/en-us/um/people/pauben/papers/wsdm2013-atypical-eickhoff-et-al.pdf
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