{"title":"A Method for Aggregating Ranked Services for Personal Preference Based Selection","authors":"K. K. Fletcher","doi":"10.4018/IJWSR.2019040101","DOIUrl":null,"url":null,"abstract":"Typically, users' service requests, which are similar with varying preferences on non-functional attributes, may result in ranked lists of services that partially meet their needs due to conflicting non-functional attributes. The resultant multiple ranked lists of services that partially satisfies the user's request makes it challenging for the user to choose an optimal service, based on his/her preference. This work proposes a method that aggregates multiple ranked lists of services into a single aggregated ranked list, where top ranked services are selected for the user. Two algorithms are proposed; 1) Rank Aggregation for Complete Lists (RACoL), that aggregates complete ranked lists and 2) Rank Aggregation for Incomplete Lists (RAIL) to aggregate incomplete ranked lists. Examples using real-world airline services to evaluate both algorithms show that the results from both proposed algorithms closely represent the sets of ranked lists better than using alternative approaches. Experiments were also carried out to validate their performance.","PeriodicalId":54936,"journal":{"name":"International Journal of Web Services Research","volume":"20 1","pages":"1-23"},"PeriodicalIF":0.8000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Web Services Research","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/IJWSR.2019040101","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 6
Abstract
Typically, users' service requests, which are similar with varying preferences on non-functional attributes, may result in ranked lists of services that partially meet their needs due to conflicting non-functional attributes. The resultant multiple ranked lists of services that partially satisfies the user's request makes it challenging for the user to choose an optimal service, based on his/her preference. This work proposes a method that aggregates multiple ranked lists of services into a single aggregated ranked list, where top ranked services are selected for the user. Two algorithms are proposed; 1) Rank Aggregation for Complete Lists (RACoL), that aggregates complete ranked lists and 2) Rank Aggregation for Incomplete Lists (RAIL) to aggregate incomplete ranked lists. Examples using real-world airline services to evaluate both algorithms show that the results from both proposed algorithms closely represent the sets of ranked lists better than using alternative approaches. Experiments were also carried out to validate their performance.
期刊介绍:
The International Journal of Web Services Research (IJWSR) is the first refereed, international publication featuring the latest research findings and industry solutions involving all aspects of Web services technology. This journal covers advancements, standards, and practices of Web services, as well as identifies emerging research topics and defines the future of Web services on grid computing, multimedia, and communication. IJWSR provides an open, formal publication for high quality articles developed by theoreticians, educators, developers, researchers, and practitioners for those desiring to stay abreast of challenges in Web services technology.