Information filtering and personalization: Context, serendipity and group profile effects

Information filtering and personalization are central to the viability of many advanced connected services that are currently being developed for mobile consumer electronic devices. The usability of these services is closely tied to their ability to offer relevant, context sensitive information while shielding the user from both information overload and missing information that she/he did not know to ask for. Furthermore, in many cases, groups of users may use such services in social situations and this dictates the need for deriving group preferences which are based on the preferences of individual group members. In this paper we present a unified information filtering and personalization model that captures the above features. In addition, we present preliminary results from a case study that provides supporting evidence for our unified model.