Many current methods of opinion mining are coarse-grained, which are practically problematic due to insufficient feedback information. To address these problems, we propose a novel topic and sentiment joint maximum entropy LDA model in this paper for fine-grained opinion mining. Considering semantic and location information of words, a maximum entropy component is first added to the traditional LDA model to distinguish background words, aspect words and opinion words. Both the local extraction and global extraction of these words are further realized. Secondly, a sentiment layer is inserted be...
