Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Original Paper
Practice and Analysis of Knowledge Construction using a Domain Ontology and Procedural Knowledge
Practice of Knowledge Construction on Musical Instrument Performance
Nami IinoSatoshi NishimuraTakuichi NishimuraKen FukudaHideaki Takeda
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JOURNAL FREE ACCESS

2020 Volume 35 Issue 1 Pages A-J44_1-12

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Abstract

This paper describes the practice of knowledge construction using a domain ontology and procedural knowledge in guitar performance. Domain ontologies are created to understand and reason the domain knowledge. However, most of them are difficult to understand ontological logic and languages for domain experts. It is important to consider the different types of knowledge representation to connect ontology experts and domain experts. In this study, we verified the effect of the knowledge construction of a domain using a domain ontology and procedural knowledge. We focused on musical instrument performance and used the knowledge of classical guitar which requires many techniques. We practiced the following processes: (1)Constructed procedural knowledge described actions of each guitar rendition in detail, (2)Developed the Guitar Rendition Ontology based on the procedural knowledge, and (3)Reconstructed the procedural knowledge with seeing the ontology by domain experts, and carried out questionnaires to them. As a result, the knowledge was increased and modified appropriately, and we received positive answers about the usefulness of the method. Constructing the domain knowledge using the two types of knowledge representation enables following aspects: (1) Domain experts can construct procedural knowledge intuitively by defining description contents and format, (2) Ontology experts can efficiently construct a domain ontology based on the procedural knowledge and (3) Domain experts can re-construct procedural knowledge with higher consistency and knowledge processing by using domain ontology together.

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© The Japanese Society for Artificial Intelligence 2020
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