A social-semantic recommender system for advertisements

作者：

Highlights：

• Ads social recommenders challenged by sparsity, cold-start and heterogeneity.

• Semantic Web technologies enable data integration and support recommendation.

• Shared ontology model aligns advertisements with users’ profiles.

• Textual contributions and network connections leveraged to improve recommendation.

• Accuracy boosted adapting user profiles to changing needs.

摘要

•Ads social recommenders challenged by sparsity, cold-start and heterogeneity.•Semantic Web technologies enable data integration and support recommendation.•Shared ontology model aligns advertisements with users’ profiles.•Textual contributions and network connections leveraged to improve recommendation.•Accuracy boosted adapting user profiles to changing needs.

论文关键词：Knowledge-based systems,Recommender systems,Natural language processing,Advertising,Social network services

论文评审过程：Received 19 July 2019, Revised 17 October 2019, Accepted 24 October 2019, Available online 5 November 2019, Version of Record 5 November 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2019.102153