Opinion Analysis of Cross-domain Product Review Based on Feature Transformation

)Traditional sentiment analysis methods aim at same domain documents, the performance becomes worse for different domain documents. To solve this problem, this paper presents an opinion analysis method of cross-domain product reviews based on feature transformation. This proposed method builds the relevance of domain dependent words between source domain and target domain via domain independent words so that it can transfer acknowledge from the source domain to the target domain. It solves the classifier performance decreasing problem due to different data distributions. The product reviews are used as a corpus in the experiment. The average accuracies are 76.61 % and 76.81 % by using the methods of Support Vector Machine(SVM) and logistic regression respectively in all corpora. The results are higher than Baseline algorithm.