QMOS: Query-based multi-documents opinion-oriented summarization
作者：
Highlights：
• It combines multiple sentiment dictionaries to improve word coverage limit.
• It integrates negation, but-clause, sarcasm, subjective/objective, question/ conditional handling.
• It integrates the semantic relations between words, and their syntactic composition to capture the meaning in comparison between a sentence and the user query.
• It expands the words in the query and sentences to tackle the problem of information limit.
• Experiment results on Blog06 & DUC2006 displayed that it is to be preferred over the existing methods.
摘要
•It combines multiple sentiment dictionaries to improve word coverage limit.•It integrates negation, but-clause, sarcasm, subjective/objective, question/ conditional handling.•It integrates the semantic relations between words, and their syntactic composition to capture the meaning in comparison between a sentence and the user query.•It expands the words in the query and sentences to tackle the problem of information limit.•Experiment results on Blog06 & DUC2006 displayed that it is to be preferred over the existing methods.
论文关键词：Sentiment analysis,Sentiment summarization,Sentiment dictionary,Contextual polarity
论文评审过程：Received 26 August 2017, Revised 2 November 2017, Accepted 8 December 2017, Available online 21 December 2017, Version of Record 21 December 2017.
论文官网地址：https://doi.org/10.1016/j.ipm.2017.12.002
