【摘要】 近年来,中文产品评论的特征情感分类是Web数据挖掘的重要研究内容之一。提出了一套完整的产品命名实体、特征词、情感词以及边界的标注规则,设计了多层次的混合标签模式;提出了双层HHMM(层级隐马尔科夫模型)结构,将词形标注和词性标注的特点进行融合;提出了基于词形标注的HHMM-1算法和基于词性标注的HHMM-2算法,实现复杂短语的自动标注。实验证明,双层HHMM模型起到了互补的作用,模型的查全率和F-score值均有较大提高。更多还原

【Abstract】 In recent years,feature and opinion classification of Chinese product review is one of the most important research fields in Web data mining.A well-defined specification on data annotation for product named entities,features,opinions and boundaries was proposed and a hybrid tag representation was designed.By integrating linguistic features and POS features into automatic learning,a novel two-level Hierarchical HMMs(HHMMs) framework was put forward.The HHMM-1 and HHMM-2 algorithms were advanced to identify features and opinion entities automatically.The experimental results showed that two-level HHMM works in a mutual complementation way,which makes the recall and F-score of our approach obviously outstanding.更多还原