期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：2
出版社：Journal of Theoretical and Applied
摘要：With the growing popularity of Web 2.0, social media is becoming the largest source of information. Because of the huge number of unstructured reviews, it is impossible to summarize all this information manually. Therefore, efficient computational methods are needed for mining and summarizing the reviews to produce a representative summarization. We presents a detailed and systematic overview of the last update in the aspect-based opinion summarization, including state-of-the-arts and methods that widely used in aspect-based opinion summarization. This paper also describes a comparison of several methods in summary generation, including text-based and visual-based opinion summarization. Finally, this paper presents some research opportunities and challenges in aspect-based opinion summarization.
关键词：Web 2.0; Social Media; Opinion Summarization; Aspect-Based Summarization.
