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. User interaction is mostly concerned with submitting initial preferences and giving feedback to suggested items . The domain of travel and tourism is more complex than others, because the products to be recommended have many facets and and context - such as the current time and location - plays a larger role. In addition, travel recommender system are often used when the user is on the road, so the user interfaces on mobile devices have to be adapted and optimized for the task. Delivering accurate and timely information is particularly valuable in these mobile scenarios such as supporting city visitors.
The goal in this Guided Research in the Informatics (or related) Master’s program (IN2169) or Application Project in the Master Data Engineering and Analytics program (IN2328) is to investigate improved solutions for user interaction in mobile applications for travel recommendation. The actual focus can be discussed and will be specific, you are welcomed to propose own ideas, options include:
- Comparing different methods for preference elicitation, e.g. questionnaire with features vs. pairwise comparison of pictures
- Investigating the trade-off between controllability (e.g. showing more features and options) and cognitive load
- User interface issues in the decision making process of users, e.g. whether how to present recommended items does change the users' choice satisfaction
- Novel approaches for visualization of the recommendation results, including map-based options
- Comparing different methods for user feedback on recommended items, e.g. rating-based vs. critiquing items
- Investigating distributed and migratory user interfaces in this domain
- Developing and testing a AR/VR prototype for eTourism
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 to allow test users to interact with the system (but no backend or actual recommender system needed)
* Conducting a user study using an appropriate method, comparing the proposed solution(s) with a baseline
The project has be to documented in a brief scientific report that can possibly be submitted to a conference or workshop. The interaction prototype can be developed in any mobile platform, e.g. Android or iOS. Prerequisites are high motivation and good programming skills in the selected mobile platform. Please send your application (brief CV, transcript of records and short motivation statement) to Wolfgang Wörndl (firstname.lastname@example.org) until Oct 3rd. The start of the project is flexible, but a guided research module has to be formally registered by the first week of a semester.
 M. Jugovac, D. Jannach: Interacting with Recommenders - Overview and Research Directions. ACM Transactions on Interactive Intelligent Systems (TiiS), 7 (3), 2017