{"title":"面向部分匹配的可伸缩Web服务组合","authors":"Adina Sirbu, J. Hoffmann","doi":"10.1109/ICWS.2008.69","DOIUrl":null,"url":null,"abstract":"We investigate scalable algorithms for automated composition (WSC) of Semantic Web Services. Our notion of WSC is very general: the composition semantics includes background knowledge and we use the most general notion of matching, partial matches, where several web services can cooperate, each covering only a part of a requirement. Unsurprisingly, automatic composition in this setting is very hard. We identify a special case with simpler semantics, which covers many relevant scenarios. We develop a composition tool for this special case. Our goal is to achieve scalability: we overcome large search spaces by guiding the search using heuristic techniques. The computed solutions are optimal up to a constant factor. We test our approach on a simple, yet powerful real world use-case; the initial results attest the potential of the approach.","PeriodicalId":275591,"journal":{"name":"2008 IEEE International Conference on Web Services","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Towards Scalable Web Service Composition with Partial Matches\",\"authors\":\"Adina Sirbu, J. Hoffmann\",\"doi\":\"10.1109/ICWS.2008.69\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We investigate scalable algorithms for automated composition (WSC) of Semantic Web Services. Our notion of WSC is very general: the composition semantics includes background knowledge and we use the most general notion of matching, partial matches, where several web services can cooperate, each covering only a part of a requirement. Unsurprisingly, automatic composition in this setting is very hard. We identify a special case with simpler semantics, which covers many relevant scenarios. We develop a composition tool for this special case. Our goal is to achieve scalability: we overcome large search spaces by guiding the search using heuristic techniques. The computed solutions are optimal up to a constant factor. We test our approach on a simple, yet powerful real world use-case; the initial results attest the potential of the approach.\",\"PeriodicalId\":275591,\"journal\":{\"name\":\"2008 IEEE International Conference on Web Services\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Web Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWS.2008.69\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Web Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWS.2008.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards Scalable Web Service Composition with Partial Matches
We investigate scalable algorithms for automated composition (WSC) of Semantic Web Services. Our notion of WSC is very general: the composition semantics includes background knowledge and we use the most general notion of matching, partial matches, where several web services can cooperate, each covering only a part of a requirement. Unsurprisingly, automatic composition in this setting is very hard. We identify a special case with simpler semantics, which covers many relevant scenarios. We develop a composition tool for this special case. Our goal is to achieve scalability: we overcome large search spaces by guiding the search using heuristic techniques. The computed solutions are optimal up to a constant factor. We test our approach on a simple, yet powerful real world use-case; the initial results attest the potential of the approach.