Recommender systems survey
作者:
Highlights:
•
摘要
Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things. This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems, identifies areas of future implementation and develops certain areas selected for past, present or future importance.
论文关键词:Recommender systems,Collaborative filtering,Similarity measures,Evaluation metrics,Prediction,Recommendation,Hybrid,Social,Internet of things,Cold-start
论文评审过程:Received 7 October 2012, Revised 4 March 2013, Accepted 19 March 2013, Available online 6 April 2013.
论文官网地址:https://doi.org/10.1016/j.knosys.2013.03.012