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Analysis of syntactic patterns for identification of features from unstructured reviews

机译:从非结构化评论中识别特征的句法模式分析

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摘要

Collecting consumer opinion about products through web is becoming more popular day by day. The opinion of users is helpful to consumers, retailors, and manufacturers in decision making. Due to the huge number user reviews it is impossible to summarize it. Therefore systems are required for mining consumer reviews data efficiently. Opinion mining is an interesting area of research due to its applications in various fields. One of the challenging issues in this area is the identification of opinion components from unstructured reviews. The work of opinion mining is natural language dependent. Therefore syntactic patterns play a key role in identifying the opinion components. In this paper we have presented analysis of synaptic patterns for products features identification from unstructured reviews. Basically the noun phrases are used for named entity identification; however all noun phrases are not features. The problem is how to restrict the patterns to get the features. After in-depth analysis and evaluation we identify a new pattern which shown comparatively best result.
机译:通过网络收集消费者对产品的意见正日益流行。用户的意见有助于消费者,零售商和制造商进行决策。由于用户评论的数量众多,因此无法对其进行总结。因此,需要系统来有效地挖掘消费者评论数据。由于其在各个领域中的应用,意见挖掘是一个有趣的研究领域。在这一领域中具有挑战性的问题之一是如何从非结构化评论中识别意见成分。意见挖掘的工作依赖于自然语言。因此,句法模式在识别意见成分中起着关键作用。在本文中,我们介绍了从非结构化评论中识别产品特征的突触模式。基本上,名词短语用于命名实体的标识;但是,所有名词短语都不是功能。问题是如何限制模式以获取功能。经过深入的分析和评估,我们确定了一种显示出相对最佳结果的新模式。

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