Sentiment Analysis Based on Collaborative Filter Attention Mechanism
ZHAO Dongmei 1,2, LI Ya2, TAO Jianhua 2, GU Mingliang1
1.School of Physics Electronic Engineering, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China; 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100101, China
Abstract：This paper investigates the influence of users personality and product information on data emotion category in review data. Among the many factors that affect the emotional data type, the subject of the evaluation, that is, the user and the object of the evaluation, are emotionally important to the commentary data. In this paper, an emotional analysis model (LSTM-CFA) based on cooperative filtering attention mechanism is proposed. The user interest distribution matrix is calculated by using the collaborative filtering (CF) algorithm. After the matrix is decomposed with SVD, the matrix is added to the hierarchical LSTM model as an attention mechanism in order to achieve emotion classification. Experiments show that the LSTM-CFA model can extract the information of users personality and product attribute efficiently, to improve the accuracy of emotion classification.
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2018, Vol. 32 
