Formal Ontology Generation by Deep Machine Learning

Shushma Patel

doi:10.1109/ICCI-CC.2017.8109723

Formal Ontology Generation by Deep Machine Learning

Shushma Patel

Research output: Contribution to conference › Paper › peer-review

16 Citations (Scopus)

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.

Original language	English
Pages	1-14
DOIs	https://doi.org/10.1109/ICCI-CC.2017.8109723
Publication status	Published - 1 Mar 2018
Externally published	Yes
Event	Cognitive Informatics & Cognitive Computing (ICCI*CC), 2017 IEEE 16th International Conference on - Duration: 3 Jan 2018 → …

Conference

Conference	Cognitive Informatics & Cognitive Computing (ICCI*CC), 2017 IEEE 16th International Conference on
Period	3/01/18 → …

Keywords

artificial intelligence
computational intelligence
machine learning
denotational semantics
formal models
concept algebra
autonomic generation
knowledge representation
Ontology
cognitive computing

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10.1109/ICCI-CC.2017.8109723Licence: CC BY 4.0

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KW - computational intelligence

KW - machine learning

KW - denotational semantics

KW - formal models

KW - concept algebra

KW - autonomic generation

KW - knowledge representation

KW - Ontology

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ER -

Formal Ontology Generation by Deep Machine Learning

Abstract

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Keywords

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