Neighborhood-Based Uncertain QoS Prediction of Web Services via Matrix Factorization

  • Guobing Zou
  • Shengye Pang
  • Pengwei Wang
  • Huaikou Miao
  • Sen Niu
  • Yanglan GanEmail author
  • Bofeng ZhangEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 268)


With the rapidly overwhelming number of services on the internet, QoS-based web service recommendation has become an urgent demand on service-oriented applications. Since there are a large number of missing QoS values in the user historical invocation records, accurately predicting these missing QoS values becomes a hot research issue. However, most existing service QoS prediction research assumes that the transactional process of the service was stable, and its QoS doesn’t change as time goes. In fact, service invocation process is usually affected by many factors (e.g., geographical location, network environment), leading to service invocations with QoS uncertainty. Therefore, QoS prediction based on traditional methods can not exactly adapt to the scenarios in real-world applications. To solve the issue, combined with the collaborative filtering and matrix factorization theory, we propose a novel approach for prediction of uncertain service QoS under the dynamic Internet environment. Extensive experiments have been conducted on a real-world data set and the results demonstrate the effectiveness and applicability of our approach for QoS prediction.


Service-oriented computing Uncertain QoS prediction Collaborative filtering Matrix factorization 



This work was partially supported by Shanghai Natural Science Foundation (No. 18ZR1414400, 17ZR1400200), National Natural Science Foundation of China (No. 61772128, 61303096), Shanghai Sailing Program (No. 16YF1400300), and Fundamental Research Funds for the Central Universities (No. 16D111208).


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.School of Computer Engineering and ScienceShanghai UniversityShanghaiChina
  2. 2.School of Computer Science and TechnologyDonghua UniversityShanghaiChina
  3. 3.Shanghai Key Laboratory of Computer Software Evaluating and TestingShanghaiChina
  4. 4.School of Computer and Information EngineeringShanghai Polytechnic UniversityShanghaiChina

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