Personalised ranking online reviews based on user individual preferences

Wei Song, Shiwei Zhang, Lizhen Liu, Hanshi Wang
{"title":"Personalised ranking online reviews based on user individual preferences","authors":"Wei Song, Shiwei Zhang, Lizhen Liu, Hanshi Wang","doi":"10.1504/IJRIS.2018.10012211","DOIUrl":null,"url":null,"abstract":"With the development of e-commerce sites, online reviews have become important data resources for e-customers. Nowadays, there have been many literatures on the category of reviews category or ranking for public. However, they only satisfy common preferences, and ignore personalised preferences of individual users. In view of this phenomenon, this paper is trying to put forward a ranking method for individual preferences. It begins with collecting the rules of user preferences by showing reviews to them to let them mark the reviews they like. Then it combines the common rules with user personalised rules to get the range of features. Finally, after calculating the optimal solution of features, the paper strives to structure a ranking model to rank reviews with the set of optimal solution.","PeriodicalId":360794,"journal":{"name":"Int. J. Reason. based Intell. Syst.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Reason. based Intell. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJRIS.2018.10012211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the development of e-commerce sites, online reviews have become important data resources for e-customers. Nowadays, there have been many literatures on the category of reviews category or ranking for public. However, they only satisfy common preferences, and ignore personalised preferences of individual users. In view of this phenomenon, this paper is trying to put forward a ranking method for individual preferences. It begins with collecting the rules of user preferences by showing reviews to them to let them mark the reviews they like. Then it combines the common rules with user personalised rules to get the range of features. Finally, after calculating the optimal solution of features, the paper strives to structure a ranking model to rank reviews with the set of optimal solution.
根据用户个人偏好对在线评论进行个性化排名
随着电子商务网站的发展,网上评论已经成为电子商务客户的重要数据资源。目前,已经有很多关于评论分类或公众排名的文献。然而,它们只满足共同的偏好,而忽略了个人用户的个性化偏好。针对这一现象,本文试图提出一种个体偏好排序方法。它首先通过向用户显示评论来收集用户偏好规则,让他们标记自己喜欢的评论。然后将通用规则与用户个性化规则相结合,得到特征范围。最后,在计算特征的最优解后,本文努力构建一个排序模型,利用最优解集对评论进行排序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信