A Joint Model for Sentiment Classification and Opinion Words Extraction

来源 :第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018) | 被引量 : 0次 | 上传用户：new_fisher

【摘要】

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【作者】

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Dawei Cong Jianhua Yuan Yanyan Zhao Bing Qin

【机构】

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Research Center for Social Computing and Information Retrieval Harbin Institute of Technology,China

【出处】

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第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

【发表日期】

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2018年9期

【关键词】

：

aspect-level sentiment analysis opinion words extraction neural network attentio

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　　In recent years,mining opinions from customer reviews has been widely explored.Aspect-level sentiment analysis is a fine-grained subtask,which aims to detect the sentiment polarity towards a partic-ular target in a sentence.While most previous works focus on senti-ment polarity classification,opinion words towards the target are also very important for that they provide details about target and contribute to judging polarity.To this end,we propose a hierarchical network for jointly modeling aspect-level sentiment classification and word-level opin-ion words extraction.Our joint model acquires superior performance in opinion words extraction and achieves comparable results in sentiment polarity classification on two datasets from SemEval 2014.

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