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Sequential patterns rule-based approach for opinion target extraction from customer reviews

机译:基于规则的基于规则的方法,用于从客户评论中提取意见目标

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摘要

Aspect extraction or opinion target extraction is the key task of sentiment analysis, which aims to identify targets of people's sentiments. This is the most important task of aspect-based sentiment analysis as without the aspects, there is no much use of extracted opinions. Recent approaches have shown the significance of dependency-based rules for the given task. These rules are heavily dependent on the dependency parser and generated with the help of grammatical rules. In this article, we are proposing to learn from user's behaviour to identify the relation among aspects and opinions. The use of sequential patterns has been proposed for the extraction of aspects. The key purpose of this research is to study the impact of sequential pattern mining in the phase of aspect extraction. Our experimental results show that the approach proposed in our work produced better results as compared with the state-of-the-art approaches.
机译:方面提取或意见目标提取是情感分析的关键任务,旨在识别人们的情感目标。这是基于方面的情感分析的最重要任务,因为没有方面,就没有太多使用提取的观点。最近的方法已经表明了基于依赖的规则对于给定任务的重要性。这些规则在很大程度上依赖于依赖性解析器,并且是在语法规则的帮助下生成的。在本文中,我们建议从用户的行为中学习以识别方面和观点之间的关系。已经提出使用顺序模式来提取方面。这项研究的主要目的是研究在方面提取阶段顺序模式挖掘的影响。我们的实验结果表明,与最新方法相比,我们工作中提出的方法产生了更好的结果。

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