基于集成特征的商品虚假评论识别模型

2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2018-08-01 DOI:10.1109/ICVRIS.2018.00103

Jing Li

{"title":"基于集成特征的商品虚假评论识别模型","authors":"Jing Li","doi":"10.1109/ICVRIS.2018.00103","DOIUrl":null,"url":null,"abstract":"More and more consumers like online shopping, and false reviews of goods mislead consumers to some extent, so it is necessary to design a false review detection method. Based on the integration characteristics of consumer history reviews, this paper proposes an online false comment detection model. The model introduces time series and combines the static and dynamic features of the reviews to detect false comments. Finally, the model is used to test the comment data of three kinds of Amazon products. The results show that the model has high recognition accuracy.","PeriodicalId":152317,"journal":{"name":"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Identification Model of Commodity False Reviews Based on Integrated Features\",\"authors\":\"Jing Li\",\"doi\":\"10.1109/ICVRIS.2018.00103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"More and more consumers like online shopping, and false reviews of goods mislead consumers to some extent, so it is necessary to design a false review detection method. Based on the integration characteristics of consumer history reviews, this paper proposes an online false comment detection model. The model introduces time series and combines the static and dynamic features of the reviews to detect false comments. Finally, the model is used to test the comment data of three kinds of Amazon products. The results show that the model has high recognition accuracy.\",\"PeriodicalId\":152317,\"journal\":{\"name\":\"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRIS.2018.00103\",\"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 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS.2018.00103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

越来越多的消费者喜欢在网上购物，而商品的虚假评论在一定程度上误导了消费者，因此有必要设计一种虚假评论检测方法。基于消费者历史评论的集成特性，提出了一种在线虚假评论检测模型。该模型引入时间序列，结合评论的静态和动态特征来检测虚假评论。最后，利用该模型对亚马逊三种产品的评论数据进行了测试。结果表明，该模型具有较高的识别精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Identification Model of Commodity False Reviews Based on Integrated Features

More and more consumers like online shopping, and false reviews of goods mislead consumers to some extent, so it is necessary to design a false review detection method. Based on the integration characteristics of consumer history reviews, this paper proposes an online false comment detection model. The model introduces time series and combines the static and dynamic features of the reviews to detect false comments. Finally, the model is used to test the comment data of three kinds of Amazon products. The results show that the model has high recognition accuracy.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)

自引率

0.00%

发文量