Earticle

초록

영어

The theory and technology of cloud computing have been widely adopted by many small and medium enterprises and individuals for their business systems or personal affairs. To facilitate the evaluation processes of cloud service creditability, the present paper proposed a new multi-attribute evaluation theory. In addition, a utility and collaborative filtering-based evaluation method was presented, which targeted actual problems existing in the processes, such as missing data or inconsistency of data dimensions. The new method utilizes Enhanced Lance and Williams Distance, which is based on Jaccard similarity coefficient, to measure the similarities between different cloud services; it also applies utility theory to data unification and integration. In the later part of this paper, simulation experiments were conducted to test the validity and rationality of the proposed method.

목차

Abstract
 1. Introduction
 2. Processes of Cloud Service Evaluation
 3. Collaborative Filtering-based Data Prediction
  3.1. Calculating Similarity of Various Cloud Services
  3.2. Choosing Similar Cloud Services
  3.3. Missing Data Prediction
 4. Utility-based Data Integration
  4.1. Data Unification
  4.2. Data Integration
 5. Case Study
  5.1. Results
  5.2. Discussions
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Xiaolong Zhu [ School of Management, Hefei University of Technology, Anhui Business Vocational College ]
• Weidong Zhu [ School of Management, Hefei University of Technology ]
• Shuai Ding [ School of Management, Hefei University of Technology ]

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