生成电子商务网站的特征级评价表,对产品进行定性评价

D.R. Kumar Raja, S. Pushpa
{"title":"生成电子商务网站的特征级评价表,对产品进行定性评价","authors":"D.R. Kumar Raja,&nbsp;S. Pushpa","doi":"10.1016/j.fcij.2017.09.002","DOIUrl":null,"url":null,"abstract":"<div><p>It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level rating for the product which is called Feature Level Review Rating Analysis (FLRRA) algorithm.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 118-124"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.09.002","citationCount":"9","resultStr":"{\"title\":\"Feature level review table generation for E-Commerce websites to produce qualitative rating of the products\",\"authors\":\"D.R. Kumar Raja,&nbsp;S. Pushpa\",\"doi\":\"10.1016/j.fcij.2017.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level rating for the product which is called Feature Level Review Rating Analysis (FLRRA) algorithm.</p></div>\",\"PeriodicalId\":100561,\"journal\":{\"name\":\"Future Computing and Informatics Journal\",\"volume\":\"2 2\",\"pages\":\"Pages 118-124\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.fcij.2017.09.002\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Computing and Informatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2314728817300326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Computing and Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2314728817300326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

今天,人们普遍认为电子商务正在迅速发展。这种情况的发生仅仅是因为人们完全依赖于已经购买和使用产品的客户给出的评级和评论。在线调查和购物网站上的客户评论是了解客户需求和反馈的关键来源,有助于提升产品质量并取得更大的成果。现在的挑战是,这些评论是来自产品级别还是功能级别,这将是一个非常重要的问题。为了克服这一问题,我们提出了一种新的产品特征等级评价算法,即特征等级评价分析(FLRRA)算法。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Feature level review table generation for E-Commerce websites to produce qualitative rating of the products

It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level rating for the product which is called Feature Level Review Rating Analysis (FLRRA) algorithm.

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
自引率
0.00%
发文量
0
期刊最新文献
Relationship between E-CRM, Service Quality, Customer Satisfaction, Trust, and Loyalty in banking Industry Enhancing query processing on stock market cloud-based database Crow search algorithm with time varying flight length Strategies for feature selection A Framework to Enhance the International Competitive Advantage of Information Technology Graduates A Literature Review on Agile Methodologies Quality, eXtreme Programming and SCRUM
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1