MT Location-based, Proactive and Decentralized Tourism Recommendation

Recommender systems recommend movies, restaurants or other items to an active user based on information about users and items. Usually, recommender systems are centralized, i.e. user ratings and all other information is stored and managed on centralized servers. However, the idea of a decentralized recommender system has some advantages, especially in mobile scenarios. In this case, users would manage their preferences, ratings, and other personal information on their mobile devices to improve user control and reduce privacy concerns. The information can then be selectively shared with other users and server-based applications to generate personal recommendations locally on the user device.

The scenario is a tourist exploring a city and proactively receiving notifications about interesting points-of-interests in the vicinity on her/his smartphone. The idea is to not only determine which items to recommend, but also when and where to recommend them. The focus of this approach is to separate personalization (i.e. management of user preferences and past behavior) from the actual recommendation. The local user model can then be used to generate personalized recommendations on the smartphone, using the global item model that includes ratings and reviews shared by other (possibly anonymized) users. Part of the project is to investigate user interaction with such a system, allowing the users to specify when or how to receive recommendations, and also which parts of their profile to share with services.

The proposed course of action in this Master's Thesis for Informatics and related fields is as follows:

• Overview of the state-of-the-art in decentralized recommender systems
• Designing a solution and implementing a prototype for the explained scenario
• Evaluating the solution from the users' perspective in a small study

Prerequisites are high motivation and good enough programming skills for the prototype. Please send your application (brief CV, transcript of records and short motivation statement) to Wolfgang Wörndl (woerndl@cit.tum.de) until March 14th. (Decision and possible start soon after this date.)