Research Article
Recommendation of Points of Interest from User Generated Data Collection
@INPROCEEDINGS{10.4108/icst.collaboratecom.2012.250451, author={Karol Waga and Andrei Tabarcea and Pasi Fr\aa{}nti}, title={Recommendation of Points of Interest from User Generated Data Collection}, proceedings={8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2012}, month={12}, keywords={recommendation relevance user collection gps trajectories routes context aware computing location based systems}, doi={10.4108/icst.collaboratecom.2012.250451} }- Karol Waga
Andrei Tabarcea
Pasi Fränti
Year: 2012
Recommendation of Points of Interest from User Generated Data Collection
COLLABORATECOM
ICST
DOI: 10.4108/icst.collaboratecom.2012.250451
Abstract
Systems that aim to predict user preferences and give recommendations are now commonly used in many systems such as online shops, social websites, and tourist guides. In this paper, we present a context aware personalized recommendation system on web and mobile, which recommends relevant location-based data from user collection and consisting of GPS routes and photos. We recommend three types of items: services, photos and GPS routes, which are points of interests in user’s surrounding. To achieve it, we score all items from database based on four aspects of relevance: location, content, time and network. In order to personalize the results we built user profile based on user’s activity in the system. We study performance of the system within MOPSI.
