Toward the most representative summaries of network user activities

A summary of a user's Internet activities, such as web visits, can closely reflect their interests and preferences. However, automating the summarization process is not trivial as it should strike a good balance between generality and specificity, while there is no gold standard for doing so. In our approach to summarizing user information, we introduce two scoring mechanisms that cooperatively optimize for polarizing criteria. Having mapped user activity information onto a category tree, the scoring mechanisms highlight the most representative tree node; the node provides an aggregated view, i.e., a summary, of the activities most representative of the user. We evaluate our approach by summarizing web activity on the network of a large cellular service provider to devise interests of individual users as well as user groups.