Markov model based mobile clickstream analysis with sub-day, day and week-scale transitions

Authors:
Toshihiko Yamakami
Affiliations:
ACCESS, Tokyo, Japan and Graduate School of Engineering, Kagawa University
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Year:
2007

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Abstract

Advanced cooperative work needs user context knowledge in spatial and temporal dimensions. The always-on property of the mobile Internet enables further extension of the cooperative work. It needs to extend the temporal knowledge of the user behaviors for this purpose. This paper explores the temporal dimension: different end-user behavior parameters in different time-scales using the mobile clickstream. The Markov model-based estimation in sub-day scale, day-scale and week-scale transition patterns is analyzed from monthly mobile clickstreams and hierarchical clustering is performed with the three different time-scale behaviors.