Emotional orientation analytical method of cross-domain texts

Abstract

The invention provides an emotional orientation analytical method of cross-domain texts, which comprises the following steps: 1) determining initial emotional points of texts and words in a source domain and a target domain; 2) respectively establishing one or more of a similarity matrix M of a test text set DU and a test word set WU and a training word set WL, a similarity matrix N of the test word set WU and the test text set DU and a training word set DL and a similarity matrix V of the test word set WU and the all word sets with relations of all word sets and all text sets according to the test text set and the test word set, and calculating a normalization matrix and a neighborhood matrix of one or more of similarity matrixes; and 3) calculating the emotional points of the test textsand the test words iteratively with the neighborhood matrix of one or more of similarity matrixes by utilizing the initial emotional points of the texts and the words in the source domain and the target domain and performing normalization. The method can improve the accuracy of the classification of the texts in a new domain substantially.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a text analysis method. Background technique [0002] In recent years, with the rapid development of the Internet, online communication platforms such as forums and blogs have emerged, and people are becoming more and more accustomed to expressing their subjective opinions on the Internet. These remarks are used to express their views and opinions on daily events, products, policies, etc. opinion, which makes there are a lot of texts with emotional tendencies on the Internet. So how to classify these texts with subjective emotions, judge whether they are positive or negative, support or oppose, this leads to an important research direction in the field of text classification - the problem of sentiment analysis. This problem has many practical applications and has become a research problem attracting more and more attention. [0003] With the rapid increase in the amount of in...

AI Technical Summary

Problems solved by technology

However, the existing methods and systems often only analyze the orientation of new domain texts based on the marked text, but the orientation analysis based only on the text is one-sided, and the knowledge of words cannot be used to improve the accuracy of orientation analysis, which often leads to low precision

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