Product features mining based on Conditional Random Fields model

Opinion mining has become a hot issue attracting the attention of many researchers recently, in which the opinion feature is essential to its modeling. In the opinion mining of products, opinion feature identification is to mine product features from product reviews. In this paper, we present a Conditional Random Fields model based Chinese product features identification approach, integrating the chunk features and heuristic position information in addition to the word features, part-of-speech features and context features. Experiments show that the proposed techniques effectively improve the performance of product opinion mining.