Filtering Algorithm for Agent-Based Incident Communication Support in Mobile Human Surveillance
MATES '08 Proceedings of the 6th German conference on Multiagent System Technologies
Latent grouping models for user preference prediction
Machine Learning
Two-Way Grouping by One-Way Topic Models
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
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In this paper we address the problem of analyzing weblog data collected at a typical online newspaper site. Wepropose a two-way clustering technique based on probability theory. On one hand the suggested method clusters thereaders of the online newspaper into user groups of similar browsing behaviour, where the clusters are determinedsolely based on the click streams collected. On the otherhand, the articles of the newspaper are clustered based onthe reading behaviour of the users. The two-way clustering produces statistical user and page profiles that can beanalyzed by domain experts for content personalization. Inaddition, the produced model can also be used for on-lineprediction so that given the user cluster of a person enteringthe site, and the page cluster of an article of a newspaper,one can infer whether or not the user will have a look at thepage in question.