基于传播的产品属性抽取

针对意见挖掘中产品意见对象的获取问题,提出一种基于传播(propagation)思想的产品属性抽取方法.该方法利用产品属性与意见词(opinion word)之间,以及产品属性本身和意见词本身的关系,通过定义的规则,抽取产品属性.对属性与意见词之间的关系采用依存语法进行描述.产品属性和意见词的抽取过程不断迭代,直至无新的属性可抽取.同时,为消除传播过程中引入的噪音,提出3种相应的噪音消除策略.实验结果表明,该方法比传统的产品属性抽取方法有更高的准确率和召回率.

Propagation based product feature extraction

To extract the targets of product opinions, we proposed a novel propagation based approach to extract product features. This approach explored the syntactic relations of opinion words and product features, opinion words and opinion words, feature and features, and defined rules to extract the features. The relations between features and opinion words are described in dependency grammar. This propagation process of feature and opinion word extraction went on until no new features could be extracted. Meanwhile, to remove possible noises introduced in the propagation, three pruning strategies were introduced. Experimental results show that it outperforms two state of the art existing approaches．