Aggregating ranked services for selection

Kenneth K. Fletcher, Xiaoqing Liu, Maggie X. Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper we propose a method for aggregating ranked services. The ranked services are generated from multiple user requests for the same service domain. First, a service search for each individual request is performed and the search results are ranked based on the user's personalized non-functional attributes and trade-offs. Next, the ranked lists of services are then aggregated and top-ranked services are selected for the user. The proposed rank aggregation method produces a consistent ranking after aggregation because it includes the rankings given by other lists for its decision making. We propose two algorithms to deal with both complete and incomplete ranked lists during service aggregation. We also present examples with real-world services to show how the service selection based on rank aggregation works and also analyzes its performance.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Services Computing, SCC 2014
EditorsElena Ferrari, Ravindran Kaliappa, Patrick C.K. Hung
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages331-338
Number of pages8
ISBN (Electronic)9781479950669
DOIs
StatePublished - Oct 17 2014
Event11th IEEE International Conference on Services Computing, SCC 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Services Computing, SCC 2014

Other

Other11th IEEE International Conference on Services Computing, SCC 2014
Country/TerritoryUnited States
CityAnchorage
Period6/27/147/2/14

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software
  • Hardware and Architecture

Keywords

  • Fuzzy set
  • Personalized trade-off preference
  • Service aggregation
  • Service selection
  • Similarity measures

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