最长评价短语及其情感评价搭配抽取方法

提出一种统计和规则相结合的最 长评价短语自动识别算法。将评价短语的识别问题转化为序列标注问题，结合条件随机场模型进行简单结构的评价短语识别，在此基础上进一步建立和应用规则库，自动识别结构复杂的最长评价短语，其测试的F值达到72.38%。在最长评价短语自动识别的基础上，构建用于 评价对象抽取和情感评价单元抽取的规则库，提出基于规则的评价搭配自动抽取算法，实现评价对象和最长评价短语搭配的自动抽取，在网易汽车门户网站进行了系统测试，得到了较高的准确率。

Method of Extracting Maximal-length Evaluation Phrase and Appraisal Expression

An algorithm based on statistics and rules is proposed to automatically identify maximal-length evaluation phrase. The identification of evaluation phrase is taken as sequence tagging problem. Then conditional random field model is used to recognize evaluation phrase with simple structure. Therefore, rule database is established and maximal-length evaluation phrase with complex structure is identified automatically. F-measure value reaches 72.38%. Based on the above work, rule base is constructed for extracting opinon target and appraisal expression. Rule-based extracting appraisal expression is proposed to automatically extract opinion target and maximal-length evaluation phrase. Experiments were conducted at netease car portal and got a higher precision.