A group recommendation approach for service selection

Tao Liu, Feng Xu, Yuan Yao, Jian Lu
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引用次数: 2

Abstract

There are more and more services that fulfill similar functionality, such as image service provided by Flickr, Picasa and Facebook. Which should be adopted to construct our software system in the open, dynamic and non-deterministic Internet environment is a key problem. Earlier work[15, 9] analyze this problem from the point view of QoS and established generic and extensible QoS computation framework for service selection. However those framework are almost designed for individuals. As social network emerges and gets widespread, people tend to be more connected and self-organize themselves into groups. Benefits of all members should be considered when we select service for group. In this article, we propose a revised group recommendation algorithm which takes advantage of collaborative filtering technology for service selection. As the experiment demonstrates, our algorithm exhibits high accuracy.
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一种服务选择的群体推荐方法
越来越多的服务实现了类似的功能,比如Flickr、Picasa和Facebook提供的图像服务。在开放、动态、不确定的网络环境下,如何构建软件系统是一个关键问题。早期的工作[15,9]从QoS的角度分析了这个问题,并建立了通用的、可扩展的QoS计算框架,用于服务选择。然而,这些框架几乎是为个人设计的。随着社交网络的出现和普及,人们倾向于更加紧密地联系在一起,并将自己组织成群体。在选择团体服务时,应考虑全体成员的利益。在本文中,我们提出了一种改进的群体推荐算法,该算法利用协同过滤技术进行服务选择。实验表明,该算法具有较高的准确率。
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Internetware 2022: 13th Asia-Pacific Symposium on Internetware, Hohhot, China, June 11 - 12, 2022 Internetware'20: 12th Asia-Pacific Symposium on Internetware, Singapore, November 1-3, 2020 Internetware '19: The 11th Asia-Pacific Symposium on Internetware, Fukuoka, Japan, October 28-29, 2019 RepoLike: personal repositories recommendation in social coding communities Effa: a proM plugin for recovering event logs
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