Abstract: A novel method is proposed to recognize the ellipsis of opinion target in Chinese text. The approach treats the task of opinion target ellipsis as a binary classification problem, which applies the machine learning algorithm. Then three kinds of features, namely position-independent features of sentence, position-dependent features of sentence and contextual features, are applied to the recognition task separately. The experimental results in three domains demonstrate that the machine learning-based method is effective for the task of the recognition of opinion target ellipsis.

Key words: sentiment analysis, opinion target extraction, ellipsis of opinion target, feature selection

摘要： 为了研究中文情感文本中评价对象省略现象的识别方法, 将评价对象省略识别建模为一个二元分类问题, 利用机器学习算法进行自动学习。探讨当前句位置无关特征、当前句位置相关特征和上下文相关特征对评价对象省略识别的作用。3个不同领域的实验结果表明, 新提出的基于机器学习的评价对象省略识别方法能够获得较好的识别效果。

关键词: 情感分析, 评价对象抽取, 评价对象省略, 特征选择