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A Learning Method based on Bisimulation in the Inconsistent Knowledge Systems

Nguyen, Thi Hong Khanh and Ha, Quang Thuy (2018) A Learning Method based on Bisimulation in the Inconsistent Knowledge Systems. In: 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), November 18-21, 201, Marina Bay Sands Expo and Convention Centre, Singapore. (In Press)

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Inconsistencies may naturally occur in the considered application domains in Artificial Intelligence, for example as a result of data mining works in distributed sources. In order to solve inconsistent knowledge, several paraconsistent description logics have been proposed. In this paper, we face the problem of concept learning for an inconsistent knowledge base system based on bisimulation. This algorithm allows learning a concept from a training information system in a paraconsistent descriptive logic system with a set of positive items, negative items, and inconsistent items. Here, we present a system for learning concept in an inconsistent knowledge base and discuss preliminary experimental results obtained in the electronic application domain.

Item Type: Conference or Workshop Item (Paper)
Subjects: Information Technology (IT)
Divisions: Faculty of Information Technology (FIT)
Depositing User: Hà Quang Thụy
Date Deposited: 17 Dec 2018 03:01
Last Modified: 17 Dec 2018 03:01

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