Research Article
Tracommender – Exploiting Continuous Background Tracking Information on Smartphones for Location-Based Recommendations
@INPROCEEDINGS{10.1007/978-3-642-36660-4_18, author={Yang Wang and Abdulbaki Uzun and Ulrich Bareth and Axel K\'{y}pper}, title={Tracommender -- Exploiting Continuous Background Tracking Information on Smartphones for Location-Based Recommendations}, proceedings={Mobile Wireless Middleware, Operating Systems, and Applications. 5th International Conference, Mobilware 2012, Berlin, Germany, November 13-14, 2012, Revised Selected Papers}, proceedings_a={MOBILWARE}, year={2013}, month={2}, keywords={location-based services background tracking recommendations path matching}, doi={10.1007/978-3-642-36660-4_18} }- Yang Wang
Abdulbaki Uzun
Ulrich Bareth
Axel Küpper
Year: 2013
Tracommender – Exploiting Continuous Background Tracking Information on Smartphones for Location-Based Recommendations
MOBILWARE
Springer
DOI: 10.1007/978-3-642-36660-4_18
Abstract
In this paper, we propose , a context-aware recommender system, which uses background tracking information from smartphones to generate location-based recommendations. Based on the automatically collected data that consist of locations with timestamps, the dwell time at certain locations can be derived in order to use it as an implicit rating for a location-based collaborative filtering. We further introduce two alternative path matching algorithms that utilize continuous location sequences (paths) to compute path patterns between similar users. In addition, in order to overcome the cold-start problem of recommender systems, clustering algorithms are used to calculate so-called - locations taken from an existing database of categorized points of interest. Synthesized movement data has been applied to perform evaluations on performance, scalability and precision of an implemented prototype of the proposed recommendation algorithms.