Towards a Context-Aware Photo Recommender System

The main challenge of recommender systems is to be able to identify and recommend items that have a greater chance of meeting the interests of their users, which generally have a very subjective and heterogeneous nature. It is imperative, then, that recommender systems, from the identification of each user's profile, could recommend personalized items. However, the user’s profile is not enough for the system to be able to completely identify the user’s interests. The use of the system in a different context from the usual may cause an unsatisfactory result for the recommendation, requiring it to be adapted to a new context. This paper presents the MMedia2U, a prototype of a mobile photo recommender system that exploits the user’s context and the context when the photo was created as a means to improve the recommendation. Three context dimensions area exploited: spatial, social and temporal. We describe the similarity measures used for each dimension and the results of the system evaluation by 13 users following a Gold Standard approach.