Cross-domain Emotion Classification Model Based on the Multi-feature Fusion

Ju Chunhua, Zou Jiangbo, Fu Xiaokang

Knowledge Management Forum ›› 2016, Vol. 1 ›› Issue (6) : 464-470.

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PDF(787 KB)
Knowledge Management Forum ›› 2016, Vol. 1 ›› Issue (6) : 464-470. DOI: 10.13266/j.issn.2095-5472.2016.054

Cross-domain Emotion Classification Model Based on the Multi-feature Fusion

  • Ju Chunhua, Zou Jiangbo, Fu Xiaokang
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Abstract

[Purpose/significance] The sentiment classification is still one of the cross-cutting issues needed to focused on.[Method/process] With the help of emotion unrelated words, by the spectral clustering algorithm, the authors constructed a cross-domain feature words emotion cluster in the source and target areas of the field. The position of the features and characteristics of emotional words, keyword features, and POS features were integrated into the logic of the regression classification algorithm to achieve a cross-cutting emotion classification algorithm based on the multi-feature fusion. [Result/conclusion] Research results show that CDFF (Cross-domain pulse Four Factors) algorithm is effective when the cross-domain user emotion is classified and its provide reference for same study.

Key words

cross-domain sentiment classification / multi-feature fusion / spectral clustering / transfer learning

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Ju Chunhua, Zou Jiangbo, Fu Xiaokang. Cross-domain Emotion Classification Model Based on the Multi-feature Fusion[J]. Knowledge Management Forum. 2016, 1(6): 464-470 https://doi.org/10.13266/j.issn.2095-5472.2016.054
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