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With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an...
This paper presents a DBN (deep belief nets) model and a multi-modality feature extraction method to extend features' dimensionalities of short text for Chinese micro blogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the micro blogging features according to the relationship between commenters and...
In this paper, Deep Belief Nets(DBN) model and Support Vector Machine(SVM) are used to mine the features hidden in social news, which can influence the emotions of men. Three feature selection methods for text modeling are used to build the input vectors of DBN, with the purpose of keeping the text information to the greatest extent. We take advantage of the deep features abstracted by DBN to build...
This paper presents an integrated method on question classification of Chinese Sichuan cuisine QA system. Classified features are extracted by means of domain attributes and the rule based classifier is constructed. SVM classifier is used for secondary classification to the questions which cannot be matched with rules. Experimental results show that the proposed method can achieve an accuracy of 96...
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