标题：Feature extraction and opinion summarization in chinese reviews
作者：Ge, Wang ;Pu, Pengbo ;Liang, Yongquan
作者机构：[Ge, Wang ;Liang, Yongquan ] College of Information Science and Engineering, Shandong University of Science and Technology, Shandong, Qingdao; 266590, 更多
来源：Open Automation and Control Systems Journal
摘要：The paper describes the process of mining opinions from Chinese reviews of products sold online. The structure of Chinese reviews is free, which leads to a more complicated relationship between opinions and features. The paper introduces two main steps of opinion mining: feature extraction and opinion direction identification. The feature extraction function first extracts “hot” features that a lot of people have express their opinions in their reviews, and then finds those infrequent ones. In order to improve the accuracy of the experiment, redundant features are removed. The opinion direction identification function takes the generated features and summarizes the opinions into two categories: positive and negative. We extract adjectives and negative adverbs as opinion words and use the Naïve Bayes classifier to identify their direction. By direction, we mean whether an opinion is positive or negative. © Ge et al.; Licensee Bentham Open.