Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/158900
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- Title
- The Prediction of trust rating based on the quality of services using fuzzy linear regression
- Related
- International Conference on Fuzzy Systems (27 - 30 June 2011 : Taipei, Taiwan)
- Related
- FUZZ-IEEE 2011 : 2011 IEEE International Conference on Fuzzy Systems : proceedings : Grand Hyatt Taipei, Taipei, Taiwan, June 27-30, 2011, p.1953-1959
- DOI
- 10.1109/FUZZY.2011.6007745
- Publisher
- Piscataway, NJ : IEEE
- Date
- 2011
- Author/Creator
- Mashinchi, M. Hadi
- Author/Creator
- Li, Lei
- Author/Creator
- Orgun, Mehmet A
- Author/Creator
- Wang, Yan
- Description
- With the advent of service-oriented computing, the issue of trust and Quality of Service (QoS) have become increasingly important. In service-oriented environments, when there are a few service providers providing the same service, a service client would be keen to know the trustworthiness of each service provider in the forthcoming transaction. The trust rating of a delivered service from a service provider can be predicted according to a set of advertised QoS data collected by the trust management authority. Although trust and QoS are qualitative by nature, most data sets represent trust and QoS in the ordinal form for the sake of simplicity. This paper introduces a new approach based on Fuzzy Linear Regression Analysis (FLRA) to extract qualitative information from quantitative data and so use the obtained qualitative information for better modeling of the data. For verification purposes, the proposed approach can be applied for the trust prediction in the forthcoming transaction based on a set of advertised QoS in service-oriented environments.
- Description
- 7 page(s)
- Subject Keyword
- Fuzzy linear regression
- Subject Keyword
- Quality of service
- Subject Keyword
- Trust prediction
- Resource Type
- conference paper
- Organisation
- Macquarie University. Dept. of Computing
- Identifier
- http://hdl.handle.net/1959.14/158900
- Identifier
- ISBN:9781424473175
- Identifier
- ISSN:1098-7584
- Identifier
- mq_res-ext-2-s2.0-80053057320
- Language
- eng
- Reviewed
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