Personalization mobile P2P network using FCA based multidimensional aggregation

Mobile applications, that cover context-aware user modeling, are becoming increasingly prevalent. In this vein, information about the users are needed for the systems in order to provide them relevant services. This information enables the systems to figure out the users and their interests. For these reasons, different applications, in several areas, organize the user's properties, preferences and interests based on a structure, called a user model, which hold all relevant user-related information. In this respect, we propose a context-based user model in mobile Peer-to-Peer (P2P) environment. This model is based on aggregating different user information like past interests and the associated context. These past interests represent information about peers from which results were obtained and which were achieved from similar queries as well as from the user context. The basic idea of our proposal is to guess correlations between past requests, past peers from which results were obtained, associated user location and user interests. The generated correlations are based upon Formal Concept Analysis. We study, the exploitation of the proposed user model in results merging task in Peer-to-Peer Information Retrieval (P2PIR).