Akshay Ratnakar, Prerna Sharma, Shruti Gupta, Dr. Lalit Purohit
{"title":"基于QoS参数的Web服务聚类","authors":"Akshay Ratnakar, Prerna Sharma, Shruti Gupta, Dr. Lalit Purohit","doi":"10.1109/AiDAS47888.2019.8970785","DOIUrl":null,"url":null,"abstract":"Due to ease of development, service oriented applications have replaced traditional web based applications. Web Services have made development easier and secure. But it is always a tough task to select the best service. Thus, web services clustering prior to selection can be useful. Before performing clustering on web services, it is desired to first determine appropriate clustering technique. In this paper, an in-depth analysis of various clustering techniques is performed. Two quality evaluation parameters, internal and stability are used. To conduct various experiments, dataset based on real world web services and dataset generated using standard available dataset generators are used.","PeriodicalId":227508,"journal":{"name":"2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Web Service Clustering on the Basis of QoS Parameters\",\"authors\":\"Akshay Ratnakar, Prerna Sharma, Shruti Gupta, Dr. Lalit Purohit\",\"doi\":\"10.1109/AiDAS47888.2019.8970785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to ease of development, service oriented applications have replaced traditional web based applications. Web Services have made development easier and secure. But it is always a tough task to select the best service. Thus, web services clustering prior to selection can be useful. Before performing clustering on web services, it is desired to first determine appropriate clustering technique. In this paper, an in-depth analysis of various clustering techniques is performed. Two quality evaluation parameters, internal and stability are used. To conduct various experiments, dataset based on real world web services and dataset generated using standard available dataset generators are used.\",\"PeriodicalId\":227508,\"journal\":{\"name\":\"2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AiDAS47888.2019.8970785\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AiDAS47888.2019.8970785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Web Service Clustering on the Basis of QoS Parameters
Due to ease of development, service oriented applications have replaced traditional web based applications. Web Services have made development easier and secure. But it is always a tough task to select the best service. Thus, web services clustering prior to selection can be useful. Before performing clustering on web services, it is desired to first determine appropriate clustering technique. In this paper, an in-depth analysis of various clustering techniques is performed. Two quality evaluation parameters, internal and stability are used. To conduct various experiments, dataset based on real world web services and dataset generated using standard available dataset generators are used.