Dionysis Athanasopoulos, A. Zarras, Panos Vassiliadis, V. Issarny
{"title":"挖掘服务抽象:NIER轨道","authors":"Dionysis Athanasopoulos, A. Zarras, Panos Vassiliadis, V. Issarny","doi":"10.1145/1985793.1985954","DOIUrl":null,"url":null,"abstract":"Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.","PeriodicalId":412454,"journal":{"name":"2011 33rd International Conference on Software Engineering (ICSE)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Mining service abstractions: NIER track\",\"authors\":\"Dionysis Athanasopoulos, A. Zarras, Panos Vassiliadis, V. Issarny\",\"doi\":\"10.1145/1985793.1985954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.\",\"PeriodicalId\":412454,\"journal\":{\"name\":\"2011 33rd International Conference on Software Engineering (ICSE)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 33rd International Conference on Software Engineering (ICSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1985793.1985954\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 33rd International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1985793.1985954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.