Generating Accurate Predictions for Unknown QoS Web Services

Miss.Ashwini Sureshrao Puri, Prof. Mansi Bhonsle


QoS-based Web service recommendation has recently gained much attention for providing a promising way
to help users find high-quality services. Collaborative filtering
is an important method for predicting missing values, and
has thus been widely adopted in the prediction of unknown
QoS values.However, collaborative filtering originated from the
processing of subjective data, such as movie scores. The QoS
data of Web services are usually objective, meaning that existing
collaborative filtering-based approaches are not always applicable
for unknown QoS values. Based on real world Web service QoS
data and a number of experiments, in this paper, we determine
some important characteristics of objective QoS datasets that
have never been found before. We propose a prediction algorithm
to realize these characteristics, allowing the unknown QoS values
to be predicted accurately. Experimental results show that the
proposed algorithm predicts unknown Web service QoS values
more accurately than other existing approaches.Comprehensive
experiments are conducted using more than 1.5 million QoS
records of real-world web service invocations. The experimental
results show the efficiency and effectiveness of our approach.

Full Text:



You Ma, Shangguang Wang, Member, IEEE, Patrick C.K. Hung, Member, IEEE, Ching-Hsien Hsu, Member, IEEE, Qibo Sun, and Fangchun

Yang, Senior Member, IEEE, A Highly Accurate Prediction Algorithm

for Unknown Web Service QoS Values , IEEE TRANSACTIONS ON

Services Computing Volume:pp 2015.

Xi Chen, Member, IEEE, Zibin Zheng, Member, IEEE, Xudong Liu,

Zicheng Huang, and Hailong Sun, Member, IEEE, Personalized QoSAware Web Service Recommendation and Visualization, IEEE TRANSACTIONS ON SERVICES COMPUTING, VOL. 6, NO. 1, JANUARYMARCH 2013.

Zibin Zheng, Student Member, IEEE, Hao Ma, Michael R. Lyu, Fellow,

IEEE, and Irwin King, Senior Member, IEEE QoS-Aware Web Service

Recommendation by Collaborative Filtering, IEEE TRANSACTIONS


Fei Peng, Xuewen Zeng, Haojiang Deng and Lei Liu The QoS Prediction

of Web Service with Location Information Ensemble, JOURNAL OF

SOFTWARE, VOL. 9, NO. 5, MAY 2014.

L.-J. Zhang, J. Zhang, and H. Cai, Services Computing. Springer and

Tsinghua Univ, 2007.

Y. Jiang, J. Liu, M. Tang, and X. Liu, ”An effective Web service

recommendation method based on personalized collaborative filtering,”

Proc. Ninth Intl Conf. Web Services (ICWS 11), pp. 211-218,2011.

S. Ran, ”A model for Web services discovery with QoS,” ACM Sigecom

exchanges, vol. 4, no. 1, pp. 1-10, 2003.

M. Tang, Y. Jiang, J. Liu, and X. Liu, ”Location-aware collaborative

filtering for qos- based service recommendation,” Proc. 10th Intl Conf.

Web Services (ICWS 12), pp. 202-209, 2012.

J. Wu, L. Chen, Y. Feng, Z. Zheng, M. C. Zhou, and Z. Wu, ”Predicting

quality of service for selection by neighborhood based collaborative

filtering,” IEEE Trans, Systems, Man, and Cybernetics: Systems, vol. 43,

pp. 428-439, 2013.

MX. Chen, X. Liu, Z. Huang, and H. Sun, ”Regionknn: A scalable

hybrid collaborative filtering algorithm for personalized Web service

recommendation,” Proc. Eighth Intl Conf. Web Services (ICWS 10), pp.

-16, 2010.

L. Shao, J. Zhang, Y. Wei, J. Zhao, B. Xie, and H. Mei, ”Personalized

qos prediction forWeb services via collaborative filtering,” Proc. Fifth Intl

Conf.Web Services (ICWS 07), pp. 439-446,2007.

D. Goldberg, D. Nichols, B. M. Oki, and D. Terry, ”Using collaborative

filtering to weave an information tapestry,” Communications of the ACM,

vol. 35, pp. 61-70, 1992.

Lina Yao, Quan Z. Sheng, Member, IEEE, Anne. H.H. Ngu, Jian Yu, and

Aviv Segev, Member, IEEE ”Unified Collaborative and Content-Based



J. Cao, Z. Wu, Y. Wang, and Y. Zhuang, ”Hybrid Collaborative Filtering

algorithm for bidirectional Web service recommendation,” Knowledge

and information systems, vol. 36, pp. 607-627, 2013.

L. Zeng, B. Benatallah, A.H. Ngu, M. Dumas, J. Kalagnanam, and H.

Chang, Qos- Aware Middleware for Web Services Composition, IEEE

Trans. Software Eng., vol. 30, no. 5, pp. 311-327, May 2004.

Jian Wu, Member, IEEE, Liang Chen, Student Member, IEEE, Yipeng

Feng, Zibin Zheng, Member, IEEE, Meng Chu Zhou, Fellow, IEEE, and

Zhaohui Wu, Senior Mem- ber, IEEE”Predicting Quality of Service for

Selection by Neighborhood-Based Collaborative Filtering”IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNET- ICS: SYSTEMS,

VOL. 43, NO. 2, MARCH 2013.

Sabanaz S. Peerzade, Vanita D. Jadhav ”A Review on Web Service Recommendation System Using Collaborative Filtering”IPASJ International

Journal of Computer Science (IIJCS)Volume 3, Issue 3, March 2015

Zibin Zheng, Hao Ma, Michael R. Lyu, and Irwin King ”WSRec: A

Collaborative Filtering Based Web Service Recommender System”2009

IEEE International Conference on Web Services.

Nikita R.Gurjar1, Sandeep V.Rode2 ”Personalized QoS-Aware Web

Service Recommendation via Exploiting Location and Collaborative Filtering”International Journal of Advanced Research in Computer Science

and Software Engineering”Volume 5, Issue 1, January 2015

Q. Yu, ”QoS-aware service selection via collaborative QoS evaluation,”

World Wide Web, vol. 17, pp. 33-57, 2014.

Ashwini Suresh Puri, Mansi Bhonsle,”A Survey of Web Service Recommendation Techniques based on QoS values”,International Journal

of Advanced Research in Computer and Communication Engineering(IJARCCE) Vol. 4, Issue 12, December 2015.

E. Costante, F. Paci, and N. Zannone, Privacy-aware web service

composition and ranking, in Proc. of the IEEE International Conference

on Web Services (ICWS), 2013, pp. 131138.

J. Zhan, C. Hsieh, I. Wang, T. Hsu, C. Liau, and D. Wang, Privacy

preserving collaborative recommender systems, IEEE Transactions on

Systems, Man, and Cybernetics, Part C, vol. 40, no. 4, pp. 472476, 2010.

L. Chen, Y. Feng, and J.Wu, ”Collaborative QoS Prediction via

Feedback-Based Trust Model,” Proc.6th Intl Conf. ServiceOriented Computing and Applications (SOCA’13), pp. 206-213, 2013.

X. Chen, X. Liu, Z. Huang, and H. Sun, ”Regionknn: A scalable

hybrid collaborative filtering algorithm for personalized Web service

recommendation,” Proc. Eighth Intl Conf. Web Services (ICWS 10), pp.

-16, 2010.


Copyright © IJETT, International Journal on Emerging Trends in Technology