现代电子技术2016，Vol.39Issue(14)：77-79,83,4.DOI:10.16652/j.issn.1004-373x.2016.14.021
基于中文微博的产品评价分类算法
Product evaluation and classification algorithm based on Chinese micro blog
摘要
Abstract
The evaluation and classification algorithm of Chinese microblog products is studied in this paper. Because the conventional support vector machine(SVM)classifier cannot satisfy the requirement of the generalization ability when the sam⁃ples are trained with a small amount of labeled data,it cannot be directly applied to the data mining of the micro blog text. And the improvement of the traditional semi supervised TSVM algorithm is accomplished by increasing the penalty function to the un⁃labeled data,but this will produce a non convex function optimization problem. Therefore,a semi⁃supervised kernel SVM classi⁃fication algorithm based on Gauss mixture model is studied in this paper. The Gauss mixture model is used to train labeled and unlabeled data to obtain the probability distribution. SVM classification algorithm can make use of the clustering information with unlabeled data as far as possible. Finally,the advantages of this research method are verified by analyzing an example of evaluation for iPhone mobile phone.关键词
微博/产品评价/数据挖掘/支持向量机/半监督学习Key words
microblog/product evaluation/data mining/support vector machine/semi-supervised learning分类
信息技术与安全科学引用本文复制引用
张燕..基于中文微博的产品评价分类算法[J].现代电子技术,2016,39(14):77-79,83,4.基金项目
国家自然科学基金地区科学基金项目（41561100）；新疆维吾尔自治区社会科学基金一般资助项目 （）
