Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of ICT Research and Applications Pub Date : 2018-04-30 DOI:10.5614/ITBJ.ICT.RES.APPL.2018.12.1.4
S. Diwandari, A. E. Permanasari, I. Hidayah
{"title":"Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining","authors":"S. Diwandari, A. E. Permanasari, I. Hidayah","doi":"10.5614/ITBJ.ICT.RES.APPL.2018.12.1.4","DOIUrl":null,"url":null,"abstract":"Visitor interaction with e-commerce websites generates large amounts of clickstream data stored in web access logs. From a business standpoint, clickstream data can be used as a means of finding information on user interest. In this paper, the authors propose a method to find user interest in products offered on e-commerce websites based on web usage mining of clickstream data. In this study, user interest was investigated using the PIE approach coupled with clustering and classification techniques. The experimental results showed that the method is able to assist in analyzing visitor behavior and user interest in e-commerce products by identifying those products that prompt visitor interest.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2018-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of ICT Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5614/ITBJ.ICT.RES.APPL.2018.12.1.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 4

Abstract

Visitor interaction with e-commerce websites generates large amounts of clickstream data stored in web access logs. From a business standpoint, clickstream data can be used as a means of finding information on user interest. In this paper, the authors propose a method to find user interest in products offered on e-commerce websites based on web usage mining of clickstream data. In this study, user interest was investigated using the PIE approach coupled with clustering and classification techniques. The experimental results showed that the method is able to assist in analyzing visitor behavior and user interest in e-commerce products by identifying those products that prompt visitor interest.
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
基于用户兴趣的基于Web使用挖掘的电子商务用户活动分析研究方法
访问者与电子商务网站的交互产生大量的点击流数据,存储在web访问日志中。从商业的角度来看,点击流数据可以用作查找用户兴趣信息的手段。在本文中,作者提出了一种基于点击流数据的web使用挖掘的方法来发现用户对电子商务网站上提供的产品的兴趣。在本研究中,使用PIE方法结合聚类和分类技术来调查用户兴趣。实验结果表明,该方法能够通过识别引起访问者兴趣的产品,帮助分析访问者对电子商务产品的行为和用户兴趣。
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 去求助
来源期刊
Journal of ICT Research and Applications
Journal of ICT Research and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
1.60
自引率
0.00%
发文量
13
审稿时长
24 weeks
期刊介绍: Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.
期刊最新文献
Smart Card-based Access Control System using Isolated Many-to-Many Authentication Scheme for Electric Vehicle Charging Stations The Evaluation of DyHATR Performance for Dynamic Heterogeneous Graphs Machine Learning-based Early Detection and Prognosis of the Covid-19 Pandemic Improving Robustness Using MixUp and CutMix Augmentation for Corn Leaf Diseases Classification based on ConvMixer Architecture Generative Adversarial Networks Based Scene Generation on Indian Driving Dataset
×
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