Interest-Driven Web Service Recommendation Based on MFI-7

Xiuwei Zhang, K. He, Chong Wang, Zhao Li, Jianxiao Liu
{"title":"Interest-Driven Web Service Recommendation Based on MFI-7","authors":"Xiuwei Zhang, K. He, Chong Wang, Zhao Li, Jianxiao Liu","doi":"10.1109/SCC.2013.69","DOIUrl":null,"url":null,"abstract":"Composing and reusing services is the main advantage of Service Oriented Software Engineering (SOSE). Faced with the large amount of Web services which are available on World Wide Web, how to select and recommend suitable Web services becomes a key issue in service computing. The most popular service recommendation technique is QoS-based Collaborate Filtering (CF) with user-service QoS matrix. However, it cannot well capture the new interests of users and handle the cold start problem. In this paper we propose an interest-driven recommendation approach which leverage User Interest Profile (UIP) to represent users' interests. UIP is generated in accordance with an ISO standard named as MFI-7. The similarity between UIPs is used to produce users' nearest neighbors. The Top-K recommendations will be generated from these neighbors' mostly-used services. To show the effectiveness of our approach, a developed Web service registry and repository platform is used as a testbed to produce preliminary evaluation results.","PeriodicalId":370898,"journal":{"name":"2013 IEEE International Conference on Services Computing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Services Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCC.2013.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Composing and reusing services is the main advantage of Service Oriented Software Engineering (SOSE). Faced with the large amount of Web services which are available on World Wide Web, how to select and recommend suitable Web services becomes a key issue in service computing. The most popular service recommendation technique is QoS-based Collaborate Filtering (CF) with user-service QoS matrix. However, it cannot well capture the new interests of users and handle the cold start problem. In this paper we propose an interest-driven recommendation approach which leverage User Interest Profile (UIP) to represent users' interests. UIP is generated in accordance with an ISO standard named as MFI-7. The similarity between UIPs is used to produce users' nearest neighbors. The Top-K recommendations will be generated from these neighbors' mostly-used services. To show the effectiveness of our approach, a developed Web service registry and repository platform is used as a testbed to produce preliminary evaluation results.
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MFI-7的兴趣驱动Web服务推荐
组合和重用服务是面向服务软件工程(SOSE)的主要优点。面对万维网上大量的Web服务,如何选择和推荐合适的Web服务成为服务计算中的一个关键问题。目前最流行的服务推荐技术是基于用户服务QoS矩阵的协同过滤(CF)。然而,它不能很好地捕捉用户的新兴趣和处理冷启动问题。本文提出了一种兴趣驱动的推荐方法,该方法利用用户兴趣档案(User Interest Profile, UIP)来代表用户的兴趣。UIP是按照名为MFI-7的ISO标准生成的。upp之间的相似性用于生成用户的最近邻居。Top-K推荐将从这些邻居最常用的服务中生成。为了显示我们的方法的有效性,我们将开发的Web服务注册中心和存储库平台用作测试平台,以产生初步的评估结果。
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
自引率
0.00%
发文量
0
期刊最新文献
IoT Mashup as a Service: Cloud-Based Mashup Service for the Internet of Things Cloud Service Negotiation: A Research Roadmap Formal Modeling of Elastic Service-Based Business Processes Security-Aware Resource Allocation in Clouds Integrated Syntax and Semantic Validation for Services Computing
×
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