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Reputation revision method for selecting cloud services based on prior knowledge and a market mechanism
Qingtao Wu1, Xulong Zhang1, Mingchuan Zhang1
1Information Engineering College, Henan University of Science and Technology, Luoyang 471023, China.
Thescientificworldjournal
|April 4, 2014
Summary
This study introduces a new method to filter unfair ratings in cloud service reputation systems. By using prior knowledge and a market mechanism, it effectively improves the accuracy of service reliability evaluations.
Area of Science:
- Computer Science
- Information Systems
- Software Engineering
Background:
- Evaluating cloud service reliability is crucial for user satisfaction.
- Objective service evaluations are challenging due to malicious ratings and user subjectivity.
- Existing reputation systems struggle with accuracy in dynamic environments.
Purpose of the Study:
- To propose a novel unfair rating filtering method for cloud service reputation systems.
- To enhance the objectivity and precision of reputation evaluations.
- To improve user satisfaction through reliable service assessments.
Main Methods:
- Developed a novel unfair rating filtering technique utilizing prior knowledge for similarity calculations.
- Integrated a market mechanism to enable dynamic adjustments by users and service providers.
- Applied the method to a reputation revision system for experimental validation.
Main Results:
- The proposed method effectively identified and filtered unfair ratings.
- Significant improvements in the precision of the reputation revision system were observed.
- The market mechanism contributed to enhanced overall system performance.
Conclusions:
- The novel filtering method enhances the reliability of cloud service reputation systems.
- Objective evaluation of cloud services is achievable with advanced filtering techniques.
- This approach offers a robust solution for maintaining trust in cloud environments.
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