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Identification of user sessions with hierarchical agglomerative clustering

2006; Wiley; Volume: 43; Issue: 1 Linguagem: Inglês

10.1002/meet.14504301312

0044-7870

Gabriel Murray, Jimmy Lin, Abdur Chowdhury,

Web Data Mining and Analysis

Abstract We introduce a novel approach to identifying Web search user sessions based on the burstiness of users' activity. Our method is user‐centered rather than population‐centered or system‐centered and can be deployed in situations in which users choose to withhold personal content information. We adopt a hierarchical agglomerative clustering approach with a stopping criterion that is statistically motivated by users' activities. An evaluation based on extracts from AOL Search™ logs reveals that our algorithm achieves 98% accuracy in identifying session boundaries compared to human judgments.