Titlebook: WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles; 4th International Wo Osmar R. Zaïane,Jaideep Srivastava,Brij Mas

严重伤害

Mining WWW Access Sequence by Matrix Clustering,ster of similar sequences. The resulting sequence elements are composed into a generalized sequence..Our method is evaluated with practical WWW access log, which shows that it is practically useful in finding long sequences and in presenting the generalized sequence in a graph.

钻孔

轻弹

PHONE

LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition, as association rules have been used in business applications. We have developed an automated method to directly infer the major groupings of user traffic on a Web site [Heer01]. We do this by utilizing multiple data features of user sessions in a clustering analysis. We have performed an extensive,

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BARGE

枫树

Muscularis

间谍活动

A Customizable Behavior Model for Temporal Prediction of Web User Sequences,ronment for users. A key prerequisite for such services is the modeling of user behavior and a natural starting place for this are Web logs. In this paper we propose a model for predicting sequences of user accesses which is distinguished by two elements: it is customizable and it reflects sequentia

MOT