An Ontology for Supporting Knowledge Discovery and Evolution

Wanyana, T and Moodley, D and Meyer, T (2020) An Ontology for Supporting Knowledge Discovery and Evolution, Proceedings of Southern African Conference for Artificial Intelligence Research, 22 - 26 February 2021, Online Digital Conference, 206-221, SACAIR 2020.

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Abstract

Knowledge Discovery and Evolution (KDE) is of interest to a broad array of researchers from both Philosophy of Science (PoS) and Artificial Intelligence (AI), in particular, Knowledge Representation and Reasoning (KR), Machine Learning and Data Mining (ML-DM) and the Agent Based Systems (ABS) communities. In PoS, Haig recently pro- posed a so-called broad theory of scientific method that uses abduction for generating theories to explain phenomena. He refers to this method of scientific inquiry as the Abductive Theory of Method (ATOM). In this paper, we analyse ATOM, align it with KR and ML-DM perspec- tives and propose an algorithm and an ontology for supporting agent based knowledge discovery and evolution based on ATOM. We illustrate the use of the algorithm and the ontology on a use case application for electricity consumption behaviour in residential households.

Item Type: Conference paper
Subjects: Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Ontology engineering
Date Deposited: 01 Sep 2021 10:01
Last Modified: 01 Sep 2021 10:01
URI: http://pubs.cs.uct.ac.za/id/eprint/1436

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