{"title":"基于PCA和SVM的电子商务网站综合评价","authors":"Zhang Caiqing, Lin Ming","doi":"10.1109/ICIII.2008.194","DOIUrl":null,"url":null,"abstract":"With the increasing use of e-commerce Web sites, it is gaining more and more attention. The evaluation of e-commerce Web sites becoming the focus of study. This paper design a comprehensive evaluation indicator system. Adopting principal component analysis method to simplify the indicator system. A evaluation model of customer relationship management system based on support vector machine was presented. Using the idea of decision binary tree, then makes the cut date to be the input information of classifier, and establish multi-classification model. By using the combination of the two methods, we will acquire a more objective and believable evaluation result. The simulation result shows that the model has better accuracy of the classification.","PeriodicalId":185591,"journal":{"name":"2008 International Conference on Information Management, Innovation Management and Industrial Engineering","volume":"501 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Evaluation of E-commerce Websites Based on PCA and SVM\",\"authors\":\"Zhang Caiqing, Lin Ming\",\"doi\":\"10.1109/ICIII.2008.194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increasing use of e-commerce Web sites, it is gaining more and more attention. The evaluation of e-commerce Web sites becoming the focus of study. This paper design a comprehensive evaluation indicator system. Adopting principal component analysis method to simplify the indicator system. A evaluation model of customer relationship management system based on support vector machine was presented. Using the idea of decision binary tree, then makes the cut date to be the input information of classifier, and establish multi-classification model. By using the combination of the two methods, we will acquire a more objective and believable evaluation result. The simulation result shows that the model has better accuracy of the classification.\",\"PeriodicalId\":185591,\"journal\":{\"name\":\"2008 International Conference on Information Management, Innovation Management and Industrial Engineering\",\"volume\":\"501 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Information Management, Innovation Management and Industrial Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIII.2008.194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Information Management, Innovation Management and Industrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIII.2008.194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comprehensive Evaluation of E-commerce Websites Based on PCA and SVM
With the increasing use of e-commerce Web sites, it is gaining more and more attention. The evaluation of e-commerce Web sites becoming the focus of study. This paper design a comprehensive evaluation indicator system. Adopting principal component analysis method to simplify the indicator system. A evaluation model of customer relationship management system based on support vector machine was presented. Using the idea of decision binary tree, then makes the cut date to be the input information of classifier, and establish multi-classification model. By using the combination of the two methods, we will acquire a more objective and believable evaluation result. The simulation result shows that the model has better accuracy of the classification.