Dynamic, behavior-based user profiling using semantic web technologies in a big data context

Abstract

The success of shaping the e-society is crucially dependent on how well technology adapts to the needs of each single user. A thorough understanding of one's personality, interests, and social connections facilitate the integration of ICT solutions into one's everyday life. The MindMinings project aims to build an advanced user profile, based on the automatic processing of a user's navigation traces on the Web. Given the various needs underpinned by our goal (e.g. integration of heterogeneous sources and automatic content extraction), we have selected Semantic Web technologies for their capacity to deliver machine-processable information. Indeed, we have to deal with web-based information known to be highly heterogeneous. Using descriptive languages such as OWL for managing the information contained in Web documents, we allow an automatic analysis, processing and exploitation of the related knowledge. Moreover, we use semantic technology in addition to machine learning techniques, in order to build a very expressive user profile model, including not only isolated "drops" of information, but inter-connected and machine-interpretable information. All developed methods are applied to a concrete industrial need: the analysis of user navigation on the Web to deduct patterns for content recommendation. © 2013 Springer-Verlag.