학술논문

Formal Ontology Generation by deep machine learning
Document Type
Conference
Source
2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) Cognitive Informatics & Cognitive Computing (ICCI*CC), 2017 IEEE 16th International Conference on. :6-15 Jul, 2017
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Handheld computers
Ontologies
Semantics
Algebra
Printers
Animals
Computational modeling
Ontology
formal models
autonomic generation
concept algebra
machine learning
knowledge representation
cognitive robot
denotational semantics
cognitive computing
AI
computational intelligence
Language
Abstract
An ontology is a taxonomic hierarchy of lexical terms and their syntactic and semantic relations for representing a framework of structured knowledge. Ontology used to be problem-specific and manually built due to its extreme complexity. Based on the latest advances in cognitive knowledge learning and formal semantic analyses, an Algorithm of Formal Ontology Generation (AFOG) is developed. The methodology of AFOG enables autonomous generation of quantitative ontologies in knowledge engineering and semantic comprehension via deep machine learning. A set of experiments demonstrates applications of AFOG in cognitive computing, semantic computing, machine learning and computational intelligence.