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QoS-Aware Web Service Recommendation by Collaborative Filtering
April-June 2011 (vol. 4 no. 2)
pp. 140-152
ASCII Text
x 
 
Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, "QoS-Aware Web Service Recommendation by Collaborative Filtering," IEEE Transactions on Services Computing, vol. 4, no. 2, pp. 140-152, April-June, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TSC.2010.52,
author = {Zibin Zheng and Hao Ma and Michael R. Lyu and Irwin King},
title = {QoS-Aware Web Service Recommendation by Collaborative Filtering},
journal ={IEEE Transactions on Services Computing},
volume = {4},
number = {2},
issn = {1939-1374},
year = {2011},
pages = {140-152},
doi = {http://doi.ieeecomputersociety.org/10.1109/TSC.2010.52},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Services Computing
TI - QoS-Aware Web Service Recommendation by Collaborative Filtering
IS - 2
SN - 1939-1374
SP140
EP152
EPD - 140-152
A1 - Zibin Zheng,
A1 - Hao Ma,
A1 - Michael R. Lyu,
A1 - Irwin King,
PY - 2011
KW - Web service
KW - collaborative filtering
KW - QoS
KW - service recommendation
KW - service selection.
VL - 4
JA - IEEE Transactions on Services Computing
ER -
 
Zibin Zheng, The Chinese University of Hong Kong, Hong Kong
Hao Ma, The Chinese University of Hong Kong, Hong Kong
Michael R. Lyu, The Chinese University of Hong Kong, Hong Kong
Irwin King, The Chinese University of Hong Kong, Hong Kong
With increasing presence and adoption of Web services on the World Wide Web, Quality-of-Service (QoS) is becoming important for describing nonfunctional characteristics of Web services. In this paper, we present a collaborative filtering approach for predicting QoS values of Web services and making Web service recommendation by taking advantages of past usage experiences of service users. We first propose a user-collaborative mechanism for past Web service QoS information collection from different service users. Then, based on the collected QoS data, a collaborative filtering approach is designed to predict Web service QoS values. Finally, a prototype called WSRec is implemented by Java language and deployed to the Internet for conducting real-world experiments. To study the QoS value prediction accuracy of our approach, 1.5 millions Web service invocation results are collected from 150 service users in 24 countries on 100 real-world Web services in 22 countries. The experimental results show that our algorithm achieves better prediction accuracy than other approaches. Our Web service QoS data set is publicly released for future research.

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Index Terms:
Web service, collaborative filtering, QoS, service recommendation, service selection.
Citation:
Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, "QoS-Aware Web Service Recommendation by Collaborative Filtering," IEEE Transactions on Services Computing, vol. 4, no. 2, pp. 140-152, April-June 2011, doi:10.1109/TSC.2010.52
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