{"title":"基于在线评论极性情绪和流形动力学方法的销售业绩预测","authors":"Zixin Dou, Yongjun Hu, Peng Cheng, Lijuan Huang, Jiuzhen Liang, Hailian Xiao","doi":"10.1109/ICSAI.2018.8599295","DOIUrl":null,"url":null,"abstract":"Online reviews provide consumers with information about products and services that may affect their purchasing decisions. As such, the customer attitude in the reviews play a important role to product sales. In this study, new sentiment prediction method is presented to enhance the forecasting accuracy by utilizing review dual-sentiments and employing non- linear manifold dynamics algorithm. Not only this method can extract and separate the polarity sentiment factors from the content of each online review, but also can remove the seasonality of products and mix the different types’ data. Extensive experimental results validate the effectiveness of our proposed method.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Predicting Sales Performance Based on Polarity Sentiments of Online Reviews and Manifold Dynamics Method\",\"authors\":\"Zixin Dou, Yongjun Hu, Peng Cheng, Lijuan Huang, Jiuzhen Liang, Hailian Xiao\",\"doi\":\"10.1109/ICSAI.2018.8599295\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online reviews provide consumers with information about products and services that may affect their purchasing decisions. As such, the customer attitude in the reviews play a important role to product sales. In this study, new sentiment prediction method is presented to enhance the forecasting accuracy by utilizing review dual-sentiments and employing non- linear manifold dynamics algorithm. Not only this method can extract and separate the polarity sentiment factors from the content of each online review, but also can remove the seasonality of products and mix the different types’ data. Extensive experimental results validate the effectiveness of our proposed method.\",\"PeriodicalId\":375852,\"journal\":{\"name\":\"2018 5th International Conference on Systems and Informatics (ICSAI)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 5th International Conference on Systems and Informatics (ICSAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAI.2018.8599295\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 5th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2018.8599295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting Sales Performance Based on Polarity Sentiments of Online Reviews and Manifold Dynamics Method
Online reviews provide consumers with information about products and services that may affect their purchasing decisions. As such, the customer attitude in the reviews play a important role to product sales. In this study, new sentiment prediction method is presented to enhance the forecasting accuracy by utilizing review dual-sentiments and employing non- linear manifold dynamics algorithm. Not only this method can extract and separate the polarity sentiment factors from the content of each online review, but also can remove the seasonality of products and mix the different types’ data. Extensive experimental results validate the effectiveness of our proposed method.
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