User profiling approaches for demographic recommender systems
作者：
Highlights：
• Many DRSs are available in our daily life and many online services will be more personalized if demographic data is taken into account.
• Unipolar or bipolar similarity measures can be used for categorical attributes profile.
• Treating age as a fuzzy variable improves the system performance and reflects the real life case.
• Results of the unified profiling approaches are almost similar with minor differences.
• Single-attribute profiling approach brings to light the advantage of each attribute of the profile.
摘要
•Many DRSs are available in our daily life and many online services will be more personalized if demographic data is taken into account.•Unipolar or bipolar similarity measures can be used for categorical attributes profile.•Treating age as a fuzzy variable improves the system performance and reflects the real life case.•Results of the unified profiling approaches are almost similar with minor differences.•Single-attribute profiling approach brings to light the advantage of each attribute of the profile.
论文关键词：Recommender system,User profile,Demographic data,Similarity computation
论文评审过程：Received 22 September 2015, Revised 4 March 2016, Accepted 5 March 2016, Available online 11 March 2016, Version of Record 2 April 2016.
论文官网地址：https://doi.org/10.1016/j.knosys.2016.03.006
