Collaborative targeting: Biclustering-based online ad recommendation

作者：

Highlights：

• Collaborative filtering methods are examined on an online advertising dataset.

• An effective method for recommending advertisements is proposed.

• Biclustering and OWA aggregation operators are used on the proposed method.

• The proposed method can recommend better ads when rich user-navigational data exist.

摘要

•Collaborative filtering methods are examined on an online advertising dataset.•An effective method for recommending advertisements is proposed.•Biclustering and OWA aggregation operators are used on the proposed method.•The proposed method can recommend better ads when rich user-navigational data exist.

论文关键词：Behavioral targeting,Biclustering,Collaborative filtering,Computational advertising,Online advertising,Ordered weighted averaging,Recommender systems

论文评审过程：Received 18 December 2018, Revised 8 May 2019, Accepted 8 May 2019, Available online 11 May 2019, Version of Record 15 May 2019.

论文官网地址：https://doi.org/10.1016/j.elerap.2019.100857