Improving Aspect Identification with Reviews Segmentation

摘要：

　　Aspect identification,a key sub-task in Aspect-Based Sentiment Analysis(ABSA),aims to identify aspect categories from online user reviews.Inspired by the observation that different segments of a review usually express different aspect categories,we propose a reviewssegmentation-based method to improve aspect identification.Specifically,we divide a review into several segments according to the sentence structure,and then automatically transfer aspect labels from the original review to its derived segments.Trained with the new constructed segment-level dataset,a classifier can achieve better performance for aspect identification.Another contribution of this paper is extracting alignment features,which can be leveraged to further improve aspect identification.The experimental results show the effectiveness of our proposed method.

关键词： Aspect identification Reviews segmentation Alignment features

作者: Tianhao Ning Zhen Wu Xin-Yu Dai Jiajun Huang Shujian Huang Jiajun Chen

作者单位: National Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China;Collaborative Innovation Center of Novel Software Technology and Industrialization,Nanjing 210023,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 416-428

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）