Improving photo recommendation with context awareness

One of the most important challenges in Information Systems is information overload. Recommender Systems try to cope with this problem by helping people in retrieving information (ex: videos, services, products, images, etc.) that may match their preferences and intentions. An issue of Recommender Systems is related to user's context. The use of the system in a different context than usual may cause an unsatisfactory result for the recommendation, since preferences and intentions can be influenced by user's context (location, trajectory, time of day, activity, etc.). This paper presents the MMedia2U, a mobile photo recommender system that exploits the user's context and the context when 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 with 13 users following a Gold Standard approach.