Fast Sentiment Analysis Algorithm Based on Double Model Fusion
Zhixing Lin1,2, Like Wang3,4, Xiaoli Cui5, Yongxiang Gu3,4,*
Computer Systems Science and Engineering, Vol.36, No.1, pp. 175-188, 2021, DOI:10.32604/csse.2021.014260
- 23 December 2020
Abstract Nowadays, as the number of textual data is exponentially increasing, sentiment analysis has become one of the most significant tasks in natural language processing (NLP) with increasing attention. Traditional Chinese sentiment analysis algorithms cannot make full use of the order information in context and are inefficient in sentiment inference. In this paper, we systematically reviewed the classic and representative works in sentiment analysis and proposed a simple but efficient optimization. First of all, FastText was trained to get the basic classification model, which can generate pre-trained word vectors as a by-product. Secondly, Bidirectional Long Short-Term More >