基于主題模型的半監督網絡文本情感分類研究

Translated title of the contribution: Study on Semi-Supervised Sentiment Classification of Web Context Based on Topic Model

李揚, 孔雯婧, 謝 邦昌

Research output: Contribution to journalArticle

Abstract

The study on the sentiment classification is challenged by the imbalanced,unmarked and nonstandard web context data.In this paper,we proposes an adaptive semi-supervised topic-based classifier to figure the above issues.Numerical study shows that the proposed method has strong adaptability to the imbalanced,unmarked datasets.A sentiment classification of hotel comment context gains effectiveness in predicting sentimental polarity of minority group in real study,which has confirmed the applicability and feasibility of this adaptive semi-supervised topic-based classifier in practical problems
Translated title of the contributionStudy on Semi-Supervised Sentiment Classification of Web Context Based on Topic Model
Original languageChinese
Journal數理統計與管理
Issue number06
Publication statusPublished - 2016

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