Ontology Development for Motorcycle Semantic Knowledge Representation

2020 ◽  
Vol 9 (2) ◽  
pp. 177
Author(s):  
I Made Cantiawan Giri Kusuma ◽  
Cokorda Rai Adi Pramartha
Keyword(s):  
System Development ◽  
Evaluation Process ◽  
Semantic Knowledge ◽  
Development Model ◽  
Ontology Development ◽  
Economic Activities ◽  
Ontology Evaluation ◽  
Object Properties ◽  
Ontology Model ◽  
Semantic Ontology

Transportation is currently a basic necessity in supporting daily life, starting from supporting economic activities and various other things. One of the most commonly used means of transportation is a motorcycle because it is very practical to use. However, the development of motorcycles is currently very fast, confusing the community in choosing a motorcycle that suits their needs. The solution used to overcome this problem can be overcome by using the concept of semantic ontology. The method of building the ontology model used is METHONTOLOGY. This method is one of the methods of building an ontology model that can reuse the built ontology for further system development. The motorcycle ontology development model generates 16 classes, 13 object properties, 11 data properties, and 69 individuals. The ontology evaluation process by performing SPARQL queries also provides appropriate results.

Ontology-based Approach for Laptop Semantic Knowledge Representation

2021 ◽  
Vol 9 (4) ◽  
pp. 485
Author(s):  
Samson Cornelius Gele Yowe ◽  
I Gede Santi Astawa
Keyword(s):  
System Development ◽  
Rapid Development ◽  
Model Development ◽  
Age Groups ◽  
Semantic Knowledge ◽  
Office Work ◽  
School Work ◽  
Ontology Model ◽  
Representation Technique ◽  
Almost All

The rapid development of technology requires everyone to adapt. It is the same as the demands of work and school so that everyone should be more able to handle this problem. It is inevitable that the use of laptops today is not something that is a step. Almost all age groups use laptops to do school work, complete office work, or as a medium of entertainment. With so many types of laptops, some people are confused about choosing a laptop. The use of ontology as an information representation technique is a solution to this problem. Ontology can present information or knowledge sources semantically and organize various information resources in a systematic and structured manner. In the development of this ontology will be made using the methontology method. Methontology is one of the ontology model development methodologies which has advantages related to a detailed description of each activity. In addition, methontology also has other advantages, namely the development of ontology that are now made usable for further system development. Therefore, this study is proposed to build an ontology model that represents knowledge about laptops.

A Systems Approach to the Design and Development of Interactive Videodisc Training

1989 ◽  
Vol 17 (4) ◽  
pp. 255-271 ◽  
Author(s):  
Jeffrey A. Cantor
Keyword(s):  
Formative Evaluation ◽  
Systems Approach ◽  
System Development ◽  
Process Analysis ◽  
Evaluation Process ◽  
Interactive Videodisc ◽  
Systematic Design ◽  
Design And Development ◽  
Test And Evaluation ◽  
Instructional Product

This article describes a four-phased process used by the U.S. Navy for the systematic design and development of interactive videodisc (IVD) courseware (ICW). Phase One of the process, Analysis and Alternatives, describes the methodology for analyzing job/task data for the purpose of verifying the appropriateness of interactive videodisc as the medium of instructional choice, and for analyzing the proposed problem, and scoping out the approach and solution. Phase Two, System Design, describes the process for the layout and design of the IVD instructional product. Phase Three, System Development, discusses the process followed to actually develop and construct an IVD system. Lastly, Phase Four, System Test and Evaluation, will describe the formative evaluation process through which the IVD product and system is proven ready for use.

Semantic and Formal Representation of Cognitive Models for the Metacognitive Architecture CARINA

2021 ◽  
pp. 54-72
Author(s):  
Alba J. Jerónimo ◽  
María P. Barrera ◽  
Manuel F. Caro ◽  
Adán A. Gómez
Keyword(s):  
Knowledge Representation ◽  
Semantic Memory ◽  
Cognitive Model ◽  
Semantic Knowledge ◽  
Cognitive Models ◽  
Formal Representation ◽  
Object Properties ◽  
Internal Information ◽  
Processing Mechanisms ◽  
The Brain

A cognitive model is a computational model of internal information processing mechanisms of the brain for the purposes of comprehension and prediction. CARINA metacognitive architecture runs cognitive models. However, CARINA does not currently have mechanisms to store and learn from cognitive models executed in the past. Semantic knowledge representation is a field of study which concentrates on using formal symbols to a collection of propositions, objects, object properties, and relations among objects. In CARINA Beliefs are a form of represent the semantic knowledge. The aim of this chapter is to formally describe a CARINA-based cognitive model through of denotational mathematics and to represent these models using a technique of semantic knowledge representation called beliefs. All the knowledge received by CARINA is stored in the semantic memory in the form of beliefs. Thus, a cognitive model represented through beliefs will be ready to be stored in semantic memory of the metacognitive architecture CARINA. Finally, an illustrative example is presented.

An Ontology based on the Methodology Proposed by Ushold and King

2016 ◽  
Vol 7 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Neha Jain ◽  
Lalit Sen Sharma
Keyword(s):  
Software Development ◽  
Ontology Engineering ◽  
Ontology Development ◽  
Semantic Technologies ◽  
Domain Specific ◽  
Development Processes ◽  
Ontology Building ◽  
Software Development Methodologies ◽  
Semantic Ontology ◽  
Standard Software

A number of methodologies are available in literature for ontology development but as the Ontology engineering field is relatively new, it is still unclear how the existing ontology building methodologies can be applied to develop semantic ontology models. In this work, firstly an overview of various ontology building methodologies and their limitations as compared to some standard software development methodologies are presented. Then the methodology proposed by Ushold and King is selected to build an ontology in e-banking domain. The challenge in this domain is to recognize, communicate and steadily improvise the banking solutions. The ontologies are prospective candidates to assist overcome these challenges and enhance interoperability of banking data and services. The study aims to provide direction for the application of existing ontology building methodologies in the Semantic Web Development processes of e-banking domain specific models which would enable their reusability and repeatability in other projects and strengthen the adoption of semantic technologies in the domain.

Towards an Operational REA Business Ontology

2009 ◽  
pp. 222-243
Author(s):  
Frederik Gailly
Keyword(s):  
Supply Chain ◽  
Information Systems ◽  
System Development ◽  
Semantic Integration ◽  
Ontology Development ◽  
Supply Chain Collaboration ◽  
Formal Representation ◽  
Heterogeneous Information ◽  
Business Information Systems ◽  
Business Information

It is widely recognized that ontologies can be used to support the semantic integration and interoperability of heterogeneous information systems. Resource Event Agent (REA) is a well-known business ontology that was proposed for ontology-driven enterprise system development. However, the current specification is neither sufficiently explicit nor formal, and thus difficult to operationalize for use in ontology- driven business information systems. In this chapter REA is redesigned and formalized following a methodology based on the reengineering extension of the METHONTOLOGY framework for ontology development. The redesign is focused on developing a UML representation of REA that improves upon existing representations and that can easily be transformed into a formal representation. The formal representation of REA is developed in OWL. The chapter discusses the choices made in redesigning REA and in transforming REA’s UML representation into an OWL representation. It is also illustrated how this new formal representation of the REA-ontology can be used to support ontology-driven supply chain collaboration.

Criminal Event Ontology Population and Enrichment using Patterns Recognition from Text

2019 ◽  
Vol 33 (11) ◽  
pp. 1940014 ◽  
Author(s):  
José A. Reyes-Ortiz
Keyword(s):  
Spanish Text ◽  
Social Networks ◽  
Pattern Recognition ◽  
Information Retrieval ◽  
Evaluation Process ◽  
Ontology Model ◽  
Important Variety ◽  
Violent Acts ◽  
Ontology Population ◽  
Event Ontology

Thousands of criminal events are reported in newspapers and social networks every day. They describe violent acts that include actors, places, times, causes and any information concerning them. Verbal and nominal phrases are used to characterize and expose criminal events, which employ an important variety of natural language structures in the newspapers. In addition, causes, times and spaces of criminal events, use linguistic phrases to represent them in text. All of them need to be extracted as a pattern recognition process in order to extract criminal events from text and the information that concerns them. The extracted events, as a knowledge base, are very useful for information retrieval tasks. Therefore, this paper presents an approach based on pattern recognition in order to extract criminal events from Spanish text, by populating and enriching an ontology model. Ontology population and enrichment involve the instantiation of criminal events and their cause relationships. An evaluation process is carried out with a set of manually tagged newspapers with categories of specific events, and shows promising results.

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