Michael Küchler just finished his master’s thesis. The goal of his master’s thesis was to investigate the benefit of following other people’s recommendations with similar or partially similar restaurant preferences. More specifically, do people follow the recommendations of other people who have overall similar preferences or share similar preferences for only specific types of restaurants (e.g., expensive italian restaurants). To this goal, Michal Küchler implemented an iPhone app and conducted a user study. To conclude, the user study showed that users of the app did not perceive both approaches (i.e., following similar users or partially similar users) as different. In fact, they didn’t care. However, users perceived following other people to find new interesting restaurants as beneficial.
Abstract of the master’s thesis
Collaborative filtering is widely used these days to filter relevant items, such as locations, movies, etc. A novel approach to collaborative Filtering is using the notion of partial user preferences in order to recommend items. Within this thesis, it is investigated how users can directly benefit from these partial preference similarities. Therefore the IPHONERECOMIZER, a mobile restaurant guide for the iPhone, was developed that (a) recommends locations based on that novel approach, and (b) bring users with overall as well as partially similar preferences in touch with each other. Within a user study, the application was evaluated in respect of these aspects, and as it turned out, the users quite like these features.
Michael Küchler: iPhoneRecomizer: exploiting partial user preference similarity for location recommendation – iOS implementation and user study, University of Zurich, Faculty of Economics, 2011. (Master Thesis)
Editors: Harald C. Gall, Amancio Bouza