Machine learning-based multi-documents sentiment-oriented summarization using linguistic treatment
作者：
Highlights：
• Machine learning-based sentiment-oriented summarization using linguistic treatment.
• Rich feature set using word embedding, sentiment, statistical, linguistic knowledge.
• We restrict proposed method in not using much domain-dependent external resources.
• It uses a deep-learning-inspired method, for the vector representation.
• Results displayed that the method is to be preferred over other methods.
摘要
•Machine learning-based sentiment-oriented summarization using linguistic treatment.•Rich feature set using word embedding, sentiment, statistical, linguistic knowledge.•We restrict proposed method in not using much domain-dependent external resources.•It uses a deep-learning-inspired method, for the vector representation.•Results displayed that the method is to be preferred over other methods.
论文关键词：Sentiment analysis,Sentiment summarization,Machine Learning,Sentiment knowledge,Word embedding
论文评审过程：Received 12 October 2017, Revised 27 March 2018, Accepted 10 May 2018, Available online 16 May 2018, Version of Record 25 May 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.05.010
