GR/AP Interactive Recommender Systems in Mobile Scenarios

Recommender systems recommend movies, restaurants or other items to an active user based on information about users and items. Research in this area does not only have to consider the underlying algorithms, but also how users interact with the systems. Delivering accurate and timely information is particularly valuable in mobile scenarios such as supporting city visitors. But the mobile domain is also more complex than others, because the products to be recommended have many facets and context - such as the current time and location - plays a larger role.

We offer several topics as Guided Research in the Informatics (or related) Master’s program (IN2169) or Application Project in the Master Data Engineering and Analytics program (IN2328) in this research area. The goal is to either investigate a mobile recommender algorithm or user interaction issues with such applications. The actual topic can be discussed and will be specific, you are welcomed to propose own ideas. The proposed course of action is as follows:

* Overview of the state-of-the-art, both in existing applications and also research literature
* Designing a solution, which can be very focused but should include some novel aspect(s)
* Implementing a prototype allowing test users to interact with the system and/or analyzing the algorithm effectiveness
* Conducting an evaluation using an appropriate method, e.g. comparing the proposed solution(s) with a baseline

The prototype application can be developed in any platform, e.g. Web-based or as a mobile application. Prerequisites are high motivation and good enough programming skills in the selected platform. Please send your application (brief CV, transcript of records and short motivation statement) to Wolfgang Wörndl (woerndl@in.tum.de). The start of the project is flexible, but a guided research module has to be formally registered by the first week of a semester.