A Novel Automatic Sentiment Summarization from Aspect-based Customer Reviews

2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2018-07-01 DOI:10.1109/JCSSE.2018.8457346

T. A. Tran, Jarunee Duangsuwan, W. Wettayaprasit

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引用次数: 3

Abstract

Online reviews play an important role in helping companies or governments to improve product quality and services. However, these reviews are increasing day by day. It is difficult to go through the amount of these reviews and to summarize the important information manually. We proposed a novel Automatic Sentiment Summarization (ASS) system. This system has two phases. The first phase is the aspect-based representation used to represent ranked knowledge on aspect opinion calculated by using frequencies, polarity, and opinion strength. The second phase is the review summary generation used to automatically produce review summary by ranking aspect based on information of the aspect. The generated summary is more coherent by applying natural language generation technique. Furthermore, the proposed ASS system allows users to add new reviews in the same domain in order to update the generated summary. The experiments used the sentiment aspect dataset benchmarks such as customer product/service reviews for Canon, Nikon, and Laptop. The generated summaries from the proposed ASS system are well performed compared with other systems extractive summarization and abstractive summarization.

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一种基于方面的顾客评论自动情感总结方法

在线评论在帮助公司或政府提高产品质量和服务方面发挥着重要作用。然而，这些评论日益增多。手动浏览这些审查的数量并总结重要信息是很困难的。提出了一种新的自动情感摘要(ASS)系统。这个系统有两个阶段。第一阶段是基于方面的表示，用于表示通过使用频率、极性和意见强度计算的方面意见上的排名知识。第二阶段是评审摘要生成，用于根据方面的信息对方面进行排序，从而自动生成评审摘要。采用自然语言生成技术生成的摘要更加连贯。此外，建议的ASS系统允许用户在同一域中添加新的评论，以便更新生成的摘要。实验使用了情感方面数据集基准，如佳能、尼康和笔记本电脑的客户产品/服务评论。与其他系统的抽取摘要和抽象摘要相比，该系统生成的摘要具有良好的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 15th International Joint Conference on Computer Science and Software Engineering (JCSSE)

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