Location History Knows What You Like : Estimation of User Preference from Daily Location Movement
Shinnosuke Wanaka(the University of Tokyo), Kota Tsubouchi
The 2nd EAI International Conference on IoT in Urban Space, 2016/5
機械学習 (Machine Learning) データサイエンス (Data Science)
- This paper describes that location log data is useful to estimate user preference and it is verified whether our hypothesis holds true. Two methods to recommend news articles using location log data are proposed. These methods are evaluated by actual application and then counting the number of articles that prove interesting to users compared with using and not using location log data. It is found that the best method for news article recommendation is the method, that labels location log data by Bayesian model "location hierarchical Dirichlet process" (LocHDP) and classifies users, thus demonstrating the usefulness of location log data in terms of news recommendation.
Location History Knows What You Like : Estimation of User Preference from Daily Location Movement（外部サイト／External Site Link）