Profiling web users preferences with text mining: Plan2See — Dynamic formulation of conceptual groups

In this paper we propose a new approach to clustering Web-based content that could be leveraged by users´ preferences. These preferences may imply grouping or dividing the initial clusters so that the resulting clusters represent users´ profiles. This approach could be applied to recommend different textual contents, based on the clusters or per user. We conduct a summarized survey of what is the state-of-the-art towards a personalized and interactive manipulation of data by users and present the general configuration of our method and some preliminary results well as the objectives for future work.