Creating recommendations on electronic books: A collaborative learning implicit approach
作者：
Highlights：
• It is possible to develop more efficient recommender systems that does not depend on users’ explicit ratings.
• It is possible to determine users’ interest by analyzing and converting their behavior.
• This approach allows to build a collective web knowledge in a co-learning context.
• This work allows to analyze the users’ behavior data and convert it into explicit ratings.
• 75.6% of data obtained by the conversion mechanism is close to optimal values.
摘要
•It is possible to develop more efficient recommender systems that does not depend on users’ explicit ratings.•It is possible to determine users’ interest by analyzing and converting their behavior.•This approach allows to build a collective web knowledge in a co-learning context.•This work allows to analyze the users’ behavior data and convert it into explicit ratings.•75.6% of data obtained by the conversion mechanism is close to optimal values.
论文关键词：Recommender system,Books recommendation,Implicit feedback,Collaborative learning
论文评审过程：Available online 8 January 2015, Version of Record 29 July 2015.
论文官网地址：https://doi.org/10.1016/j.chb.2014.10.057
