图 书 馆
一种应用于论文的情绪分析的混合方法A Hybrid Approach for Sentiment Analysis Applied to Paper |
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| 课程网址: | http://videolectures.net/kdd2017_keith_hybrid_approach/ |
| 主讲教师: | Brian Keith |
| 开课单位: | 北天主教大学 |
| 开课时间: | 2017-12-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This article discusses the problem of extracting sentiment and opinions about a collection of articles on scientific reviews conducted under an international conference on computing in Spanish language. The aim of this analysis is on the one hand to automatically determine the orientation of a review of an article and contrast this approach with the assessment made by the reviewer of the article. This would allow scientists to characterize and compare reviews crosswise, and more objectively support the overall assessment of a scientific article. A hybrid approach that combines an unsupervised machine learning algorithm with techniques from natural language processing is proposed to analyze reviews, and part-of-speech (POS) tagging to obtain the syntactic structure of a sentence. This syntactic structure, along with the use of dictionaries, allows to determine the semantic orientation of the review through a scoring algorithm. A set of experiments were conducted to evaluate the capability and performance of the proposed approaches relative to a baseline, using standard metrics, such as accuracy, precision, recall, and the F1-score. The results show improvements in the case of binary, ternary and a 5-point scale classification in relation to classical machine learning algorithms such as SVM and NB, but they also present a challenge to improve the multiclass classification in this domain. |
| 关 键 词: | 情绪分析; 论文应用; 混合方法; 评估文章 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-05-24：chenxin01 |
| 最后编审: | 2023-05-24：chenxin01 |
| 阅读次数: | 16 |