Chinese Explanatory Opinionated Sentence Recognition Based on Auto-Encoding Features
Yuan He · Beijing Daxue Xuebao. Zirankexueban · 2015
An auto-encoding feature based classification method to Chinese explanatory opinionated sentence recognition was presented. An explanatory opinion corpus is built firstly from online product reviews in cellphone and car domains. Then, word embeddings are learned from product reviews using the auto-encoding technique. Finally, the learned word embeddings are used as features for explanatory opinionated sentence classification under the framework of supported vector machines. Experimental results show that word embeddings are more effective than some traditional representations of features like Chi-square, TF-IDF and information gains for explanatory opinionated sentence classification.