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Subjectivity detection aims to distinguish natural language as either opinionated (positive or negative) or neutral. In word vector based convolutional neural network models, a word meaning is simply a signal that helps to classify larger entities such as a document. Previous works do not usually consider prior distribution when using sliding windows to learn word embedding's and, hence, they are...
With rapid development of E-commerce platforms, automated review sentiment analysis for commodities becomes a research focus, with main purpose to extract potential information within reviews for decision making of consumers. Traditional methods have made some progress on document level sentiment analysis, but with tremendous increasing of data scale, how to process high dimension of data fast and...
Related research for sentiment analysis on Chinese microblog is aiming at analyzing the emotion of posters. This paper presents a content extension method that combines post with its' comments into a microblog conversation for sentiment analysis. A new convolutional auto encoder which can extract contextual sentiment information from microblog conversation of the post is proposed. Furthermore, a DBN...
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