Interest-based recommendations for business intelligence users

作者:

Highlights:

• A simple formal model of BI interactions.

• The learning of a similarity measure based on features characterizing BI user interests.

• An approach to automatically discover user interests based on our measure.

• A recommender system designed to take advantage of the discovered user interests.

• An extensive set of experiments for the tuning and validation of our approach through a user study.

摘要

•A simple formal model of BI interactions.•The learning of a similarity measure based on features characterizing BI user interests.•An approach to automatically discover user interests based on our measure.•A recommender system designed to take advantage of the discovered user interests.•An extensive set of experiments for the tuning and validation of our approach through a user study.

论文关键词:User interest,Feature construction,Clustering,BI analyses,Collaborative recommender systems

论文评审过程:Received 30 November 2017, Revised 16 May 2018, Accepted 13 August 2018, Available online 11 September 2018, Version of Record 30 July 2019.

论文官网地址:https://doi.org/10.1016/j.is.2018.08.004