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Identification of user sessions with hierarchical agglomerative clustering

✍ Scribed by G. Craig Murray; Jimmy Lin; Abdur Chowdhury

Publisher
Wiley (John Wiley & Sons)
Year
2007
Tongue
English
Weight
83 KB
Volume
43
Category
Article
ISSN
0044-7870

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✦ Synopsis

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.

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