计算机应用研究2016，Vol.33Issue(5)：1308-1311,4.DOI:10.3969/j.issn.1001-3695.2016.05.006
面向在线产品评论数据的有效性建模与测度研究
Modeling and measure research for online product review data
摘要
Abstract
To analyze online reviews effectively and provide valuable information to both consumers and companies,this paper proposed data modeling and measure system for online product reviews.Firstly,this paper proposed the identifying method based on the KPCA-LS-SVM(kernel principal component analysis least squares support vector machine)model for fake reviews problem.Meanwhile,the paper solved the problem of review data validation analysis by ordinal logistic probability model for the problem of review data validation analysis.At last,experiments were conducted on the real dataset.The results show that it not only can effectively classify fake online reviews,but also improve discriminant validity of the data efficiently.关键词
在线产品评论/核主成分分析/虚假评论识别/排序Logistic/有效性分析Key words
online product review/kernel principal component analysis/fake review identification/ordinal Logistic/effi-ciency analysis分类
信息技术与安全科学引用本文复制引用
唐塞丽,仙树,胡蕾,刘猛,代坤..面向在线产品评论数据的有效性建模与测度研究[J].计算机应用研究,2016,33(5):1308-1311,4.基金项目
国家自然科学基金资助项目（71272018）；国家自然科学基金（地区基金）资助项目 （）
