Earticle

초록

영어

With the increasing abundance of Web Services across Internet, Quality of Service (QoS)-based service recommendation has become a hot issue. It is necessary to predict the missing values of QoS for service recommendation. Because Web services run on the Internet, their network locations may be anther critical factor for QoS prediction. Although there have existed many works on QoS prediction, few consider the influence of the network locations of users or Web Services. In this paper, we propose a novel collaborative QoS prediction framework with network location-based regularization (NLBR). We first elaborate the popular Matrix Factorization (MF) model for missing values prediction. Then, by taking advantage of the local connectivity between Web services users, we incorporate network location information to identify the neighborhood. We conduct the experiments on a public large-scale real-world QoS dataset, Experiments show that our proposed approaches have the better prediction performance compared with the existed approaches.

목차

Abstract
 1. Introduction
 2. A Motivating Scenario
 3. Location Information Representation, Acquisition and Processing
 4. Matrix Factorization Model
 5. Network Location-Based Regularization
  5.1. Notations and Definitions
  5.2. Neighborhood Similarity Computation
  5.3. Network Location-Based Regularization (NLBR)
 6. Discussion
 7. Experiments
  7.1. Experimental Setup
  7.2. Metrics
  7.3. Comparison
  7.4. Impact of K
  7.5. Impact of γ
  7.6. Impact of Dimensionality
  7.7. Impact of Matrix Density
 8. Related Work
 9. Conclusion and Future Work
 Acknowledgement
 References

키워드

저자

• Li Zhou [ School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China, Key Laboratory of Complex System Modeling and Simulation, Ministry of Education ]
• Zhibo Song [ School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China, Key Laboratory of Complex System Modeling and Simulation, Ministry of Education ]
• Suichu Zhai [ Hangzhou Power Supply Cooperation, Hangzhou, China ]
• Tan Xiao [ Hangzhou Power Supply Cooperation, Hangzhou, China ]
• Yuyu Yin [ School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China, Key Laboratory of Complex System Modeling and Simulation, Ministry of Education, Electric Engineering School, Zhejiang University, Hangzhou, China ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605