Title :
UCOS: Enhanced Online Skyline Computation by User Clustering
Author :
Kehan Chen ; Lichuan Ji ; Kunyang Jia ; Jian Wu
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China
fDate :
June 28 2013-July 3 2013
Abstract :
In this paper, we propose a skyline computation system UCOS (User Clustering based Online Skyline), which divides the computation into offline and online stages. Based on the truth that QoS similarity implies the skyline similarity, the offline stage of UCOS system dose user clustering according to the historical user-service QoS records by given distance metrics. Then, we compute the representative skyline for each cluster standing for the general characters of the users´ skylines. Benefit from those offline results, the online stage is able to give a rapid prediction for online skyline request and achieves good online computation performance by doing refinement on the predicted results.
Keywords :
Web services; pattern clustering; quality of service; QoS similarity; UCOS skyline computation system; distance metrics; historical user-service QoS records; offline computation stage; online computation stage; online skyline request; quality of service; user clustering based online skyline; Clustering algorithms; Computer architecture; Conferences; Educational institutions; Measurement; Prediction algorithms; Quality of service; Clustering; QoS; Service Selection; Skyline;
Conference_Titel :
Services Computing (SCC), 2013 IEEE International Conference on
Conference_Location :
Santa Clara, CA
Print_ISBN :
978-0-7695-5026-8
DOI :
10.1109/SCC.2013.14
