{"title":"WSBen:一个Web服务发现和组合基准","authors":"Seog-Chan Oh, Dongwon Lee","doi":"10.4018/jwsr.2009092301","DOIUrl":null,"url":null,"abstract":"A novel benchmark, WSBen, for testing Web services discovery and composition is presented. WSBen includes: (1) a collection of synthetic Web services (WSDL) files with diverse characteristics and sizes; (2) test discovery and composition queries and solutions; and (3) external files for statistical analysis and AI planners. Users can fine-tune the generated WSDL files using various parameters such as skewness or matching type. It is our hope that WSBen provides useful insights for researchers evaluating the performance of Web services discovery and composition algorithms and software","PeriodicalId":408032,"journal":{"name":"2006 IEEE International Conference on Web Services (ICWS'06)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"72","resultStr":"{\"title\":\"WSBen: A Web Services Discovery and Composition Benchmark\",\"authors\":\"Seog-Chan Oh, Dongwon Lee\",\"doi\":\"10.4018/jwsr.2009092301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel benchmark, WSBen, for testing Web services discovery and composition is presented. WSBen includes: (1) a collection of synthetic Web services (WSDL) files with diverse characteristics and sizes; (2) test discovery and composition queries and solutions; and (3) external files for statistical analysis and AI planners. Users can fine-tune the generated WSDL files using various parameters such as skewness or matching type. It is our hope that WSBen provides useful insights for researchers evaluating the performance of Web services discovery and composition algorithms and software\",\"PeriodicalId\":408032,\"journal\":{\"name\":\"2006 IEEE International Conference on Web Services (ICWS'06)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"72\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Conference on Web Services (ICWS'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/jwsr.2009092301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Web Services (ICWS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/jwsr.2009092301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
WSBen: A Web Services Discovery and Composition Benchmark
A novel benchmark, WSBen, for testing Web services discovery and composition is presented. WSBen includes: (1) a collection of synthetic Web services (WSDL) files with diverse characteristics and sizes; (2) test discovery and composition queries and solutions; and (3) external files for statistical analysis and AI planners. Users can fine-tune the generated WSDL files using various parameters such as skewness or matching type. It is our hope that WSBen provides useful insights for researchers evaluating the performance of Web services discovery and composition algorithms and software
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