Recommendations-based on semantic analysis of social networks in learning environments

作者：

Highlights：

• Fully automatic learning framework based on web semantics.

• Grouping the users communities by extracting their common and individual interests.

• Intelligent recommendations, based on the analysis of the interactions between users and communities.

• Capture the underlying semantics of the users feelings and needs.

• Guiding learners by recommending the best learning resources and practices.

摘要

•Fully automatic learning framework based on web semantics.•Grouping the users communities by extracting their common and individual interests.•Intelligent recommendations, based on the analysis of the interactions between users and communities.•Capture the underlying semantics of the users feelings and needs.•Guiding learners by recommending the best learning resources and practices.

论文关键词：Web semantics,Web 2.0,Social network analysis,Social learning networks,User's behavior,Community detection

论文评审过程：Received 31 March 2018, Revised 3 July 2018, Accepted 27 August 2018, Available online 31 August 2018, Version of Record 16 September 2019.

论文官网地址：https://doi.org/10.1016/j.chb.2018.08.051