{"title":"一种服务选择的群体推荐方法","authors":"Tao Liu, Feng Xu, Yuan Yao, Jian Lu","doi":"10.1145/2430475.2430485","DOIUrl":null,"url":null,"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.","PeriodicalId":20631,"journal":{"name":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","volume":"10 1","pages":"10:1-10:5"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A group recommendation approach for service selection\",\"authors\":\"Tao Liu, Feng Xu, Yuan Yao, Jian Lu\",\"doi\":\"10.1145/2430475.2430485\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":20631,\"journal\":{\"name\":\"Proceedings of the 8th Asia-Pacific Symposium on Internetware\",\"volume\":\"10 1\",\"pages\":\"10:1-10:5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th Asia-Pacific Symposium on Internetware\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2430475.2430485\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th Asia-Pacific Symposium on Internetware","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2430475.2430485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A group recommendation approach for service selection
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.