@inproceedings{26124d5d0a8e40cb82c316b4eb1a1372,
title = "Aggregating ranked services for selection",
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.",
keywords = "Fuzzy set, Personalized trade-off preference, Service aggregation, Service selection, Similarity measures",
author = "Fletcher, {Kenneth K.} and Xiaoqing Liu and Cheng, {Maggie X.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 11th IEEE International Conference on Services Computing, SCC 2014 ; Conference date: 27-06-2014 Through 02-07-2014",
year = "2014",
month = oct,
day = "17",
doi = "10.1109/SCC.2014.51",
language = "English (US)",
series = "Proceedings - 2014 IEEE International Conference on Services Computing, SCC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "331--338",
editor = "Elena Ferrari and Ravindran Kaliappa and Hung, {Patrick C.K.}",
booktitle = "Proceedings - 2014 IEEE International Conference on Services Computing, SCC 2014",
address = "United States",
}