• Smart Media Journal
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• v.9 no.2
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• pp.51-62
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• 2020

Starting with the "Smart Grid National Road Map" in 2010, the Smart Grid 2030 was introduced through the basic plan and implementation plan of the intelligent power grid with the goal of building the world's first national smart grid. In this paper, we intend to build a power domain ontology based on the power business platform based on the upper and lower conceptual models of the "Smart Grid Interoperability Standard Framework and Roadmap", the standard of implementation plan. Ontology is suitable for expressing and utilizing the smart grid conceptual model because it considers hierarchical structure as knowledge defines the properties of entities and relationships between entities, but there is no research related to them. Therefore, in this paper, the upper ontology was defined as a major category for smart grid-related fields, and the lower ontology was defined as detailed systems and functions for the upper ontology to construct the ontology. In addition, scenarios in various situations that could occur in the power system were constructed and significant inference results were derived through inference engines and queries.

• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.41-56
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• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.321-330
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• 2023

In this paper, we propose a method of automatically creating an ontology by extracting various relationships between terms necessary for constructing an ontology of a specific domain. The extracted relationship is constructed as an ontology by encoding it into an axiomatic set in the structure of the ontology. To solve efficiently, we represent the search space of the set as an integer programming problem, and we reduce the matrix by using a simple reduction that eliminates rules that are not very helpful for optimization. In conclusion, this paper proposes a way to generalize patterns using given data, reduce search space while maintaining useful patterns, and automatically generate efficient ontology using extracted relationships by applying algorithms composed of structured ontology.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.376-380
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• 2018

Objectives: This research presents the design and development of a software architecture using natural language processing tools and the use of an ontology of knowledge as a knowledge base. Methods: The software extracts, manages and represents the knowledge of a text in natural language. A corpus of more than 200 medical domain documents from the general medicine and palliative care areas was validated, demonstrating relevant knowledge elements for physicians. Results: Indicators for precision, recall and F-measure were applied. An ontology was created called the knowledge elements of the medical domain to manipulate patient information, which can be read or accessed from any other software platform. Conclusions: The developed software architecture extracts the medical knowledge of the clinical histories of patients from two different corpora. The architecture was validated using the metrics of information extraction systems.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.5
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• pp.1151-1156
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• 2003

To obtain both of the fast and complete data entry and the acquisition of reusable data in a Computer-based Patient Record system (CPR), we are building the ontology that is used by the entry supporting agents. Our application domain is Traditional Chinese Medicine. As the tool for the implementation, we used protege 2000 which is ontology building tool and provides frame knowledge representation language. In this paper, the construction methodology of our ontology is reported.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.271-286
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• 2008

The core of the semantic web is ontology, which supports interoperability among semantic web applications and enables developer to reuse and share domain knowledge. It used a variety of fields such as Information Retrieval, E-commerce, Software Engineering, Artificial Intelligence and Bio-informatics. However, the reality is that various errors might be included in conceptual hierarchy when developing ontologies. Therefore, methodologies and supporting tools are essential to help the developer construct suitable ontologies for the given purposes and to detect and analyze errors in order to verify the inconsistency in the ontologies. In this paper we propose a new approach for ontology error detection based on the Concept Lattices of Formal Concept Analysis. By using the tool that we developed in this research, we can extract core elements from the source code of Ontology and then detect some structural errors based on the concept lattices. The results of this research can be helpful for ontology engineers to support error detection and construction of "well-defined" and "good" ontologies.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.197-203
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• 2003

The purpose of the study is to develop an integrated knowledge structuring system for the domain of engineering, in which ontology-based literature mining, knowledge acquisition, knowledge integration, and knowledge retrieval are combined using XML-based tag information and ontology management. The system supports combining different types of databases (papers and patents, technologies and innovations) and retrieving different types of knowledge simultaneously. The main objective of the system is to facilitate knowledge acquisition and knowledge retrieval from documents through an ontology-based dynamic similarity calculation and a visualization of automatically structured knowledge. Through experimentations we conducted using 100,000 words economic documents reported in the "Go！ Japan" project for analyzing Japanese industrial situation, and 100,000 words molecular biology Papers, we show the system is Practical enough for accelerating knowledge acquisition and knowledge discovery from the information sea.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.803-804
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• 2009

To accommodate constantly growing knowledge in scientific discourse that is revised over time by domain experts, we need to also evolve our ontology. The body of knowledge will get structured and refined as we develop a deeper understanding of issues. Keeping trail of new changes in semantically rich and formally sound mechanism has pragmatic advantages for providing the undo and redo facility and ontology recovery to a previous state. In this research, we have proposed a framework that support change logging and then using these logged changes for reverting ontology to a previous consistent state and visualization of change effects on ontology. The system is compared with ChangesTab of $Prot{\acute{e}}g{\acute{e}}$ and the results depict better accuracy for our system.

• Journal of KIISE
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• v.42 no.5
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• pp.580-590
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• 2015

Recently, the issue of efficient power management in datacenters as a part of green computing has gained prominence. For realizing efficient power management, effective power monitoring and analysis must be conducted for servers in a datacenter. However, an administrator should know the exact structure of the datacenter and its associated databases, and is required to analyze relationships among the observed data. This is because according to previous monitoring approaches, servers are usually managed using only databases. In addition, it is not possible to monitor data that are not indicated in databases. To overcome these drawbacks, we proposed an ontology-based monitoring approach. We constructed domain ontology for management servers at a datacenter, and mapped observed data onto the constructed domain ontology by using semantic annotation. Moreover, we defined query creation rules and server state rules. To demonstrate the proposed approach, we designed an ontology based monitoring system architecture, and constructed a knowledge system. Subsequently, we implemented the pilot system to verify its effectiveness.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.437-448
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• 2004

This paper presents an approach to the development of bio-ontology using the Object-oriented Ontology Manager(OOM). OOM views a term of an ontology as an object which can be an instance or a concept. OOM facilitates the semi-automatic construction of ontologies by an intuitive interface and by inferencing with links among complicated and informative ontology terns. The main advantage of OOM is simple-to-use not compromising expressiveness so that ontologies in a complicated domain such as bioinformatics can be modeled intuitively. The ontologies constructed by OOM are easily exported to ontologies in other ontology languages without semantic loss because the structures of both the ontology by OOM and the ontologies in most of standard ontology languages are analogous. A translator to another standard ontology language is also provided by OOM so that the ontology can be combined with others to be applied to more complicated applications.