基于混合类别序列规则的中文比较评论的识别

在线评论中的比较信息揭示了品牌和商品的竞争性关系，为消费者的购买决策提供了有力的依据。在线评论中比较信息通常以显性和隐性两种形式存在。为此，提出一种将句法、规则、特征相结合的比较句识别算法。针对显性比较评论，提出了融合CSR方法与依存句法分析算法，即比较句的形式化结构与内在依存关系两方面结合，提高比较句识别的效率。针对隐性比较评论，提出了基于产品名识别的方法，可有效识别隐性比较句，由此拓宽了比较句识别的范围。以京东购物平台为数据来源，实验表明，本文方法在比较关系识别上获得了较好的效果。

Identification of Comparative Information from Chinese Online Reviews Based on a Hybrid Class Sequential Rules Method

Comparative information found in online reviews can reveal the competitive relations between brands and commodities, providing a strong basis for consumers to make purchase decisions. Usually, comparative information exists either in an explicit way or in an implicit way. Thus, this paper intends to propose a hybrid algorithm for identifying comparative sentences, which combines syntax, rules, and features. In order to identifying explicit comparison comments, it raises an algorithm combining the CSR algorithm and the dependency parsing method. The proposed algorithm enables the improvement of efficiency for comparative sentence recognition by comparing structure and syntax between sentences. Regarding implicit comparison comments, it proposes a method based on product name recognition to effectively identify the implicit comparison sentences by using the data from the online reviews in JD.com website. The experiment results show that the proposed method can achieve significant improvement in identifying comparative online reviews.