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 contribution | Study on Semi-Supervised Sentiment Classification of Web Context Based on Topic Model |
|---|---|
| Original language | Chinese |
| Journal | 數理統計與管理 |
| Issue number | 06 |
| Publication status | Published - 2016 |