Neural network for learning and analyzing preferences for Multi-Criteria services

Neural network for learning and analyzing preferences for Multi-Criteria services

연구 분야: Verification

학회: SITA'20: Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications

In the latest years, service selection is becoming more and more important due to the significant effect of internet based services in the telecom industry. When it comes to selecting the best service, different candidate services with similar settings are proposed by different service providers. The selection should take into consideration the respect of the constraints of consumers in terms of Service Level Agreement contracts, what makes the modelling of the preferences of decision-makers for choice problems the main focus of this work. In order to model these preferences, we propose contextual preference functions based on machine learning techniques from neural networks. It will therefore be possible to further explain and decode preferences in order to facilitate negotiation and thus decision-making, thereby improving the quality of service providers while being on customer preferences.