Social context summarization using user-generated content and third-party sources
作者：
Highlights：
• A novel framework for social context summarization is proposed.
• The framework relies on the reinforcement support of external information.
• 23 features in three groups: local, user-generated, and third-party are proposed.
• A new open-domain dataset is created and manually annotated.
• Combining internal and external information benefits the summarization.
摘要
•A novel framework for social context summarization is proposed.•The framework relies on the reinforcement support of external information.•23 features in three groups: local, user-generated, and third-party are proposed.•A new open-domain dataset is created and manually annotated.•Combining internal and external information benefits the summarization.
论文关键词：Data mining,Information retrieval,Document summarization,Social context summarization,Learning to rank
论文评审过程：Received 1 June 2017, Revised 18 December 2017, Accepted 22 December 2017, Available online 28 December 2017, Version of Record 14 February 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2017.12.023
