• Asia pacific journal of information systems
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• v.20 no.2
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• pp.125-155
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• 2010

Ontologies have been adopted in various business and scientific communities as a key component of the Semantic Web. Despite the increasing importance of ontologies, ontology developers still perceive construction tasks as a challenge. A clearly defined and well-structured methodology can reduce the time required to develop an ontology and increase the probability of success of a project. However, no reliable knowledge-engineering methodology for ontology development currently exists; every methodology has been tailored toward the development of a particular ontology. In this study, we developed a Graduation Screen Ontology (GSO). The graduation screen domain was chosen for the several reasons. First, the graduation screen process is a complicated task requiring a complex reasoning process. Second, GSO may be reused for other universities because the graduation screen process is similar for most universities. Finally, GSO can be built within a given period because the size of the selected domain is reasonable. No standard ontology development methodology exists; thus, one of the existing ontology development methodologies had to be chosen. The most important considerations for selecting the ontology development methodology of GSO included whether it can be applied to a new domain; whether it covers a broader set of development tasks; and whether it gives sufficient explanation of each development task. We evaluated various ontology development methodologies based on the evaluation framework proposed by G$\acute{o}$mez-P$\acute{e}$rez et al. We concluded that METHONTOLOGY was the most applicable to the building of GSO for this study. METHONTOLOGY was derived from the experience of developing Chemical Ontology at the Polytechnic University of Madrid by Fern$\acute{a}$ndez-L$\acute{o}$pez et al. and is regarded as the most mature ontology development methodology. METHONTOLOGY describes a very detailed approach for building an ontology under a centralized development environment at the conceptual level. This methodology consists of three broad processes, with each process containing specific sub-processes: management (scheduling, control, and quality assurance); development (specification, conceptualization, formalization, implementation, and maintenance); and support process (knowledge acquisition, evaluation, documentation, configuration management, and integration). An ontology development language and ontology development tool for GSO construction also had to be selected. We adopted OWL-DL as the ontology development language. OWL was selected because of its computational quality of consistency in checking and classification, which is crucial in developing coherent and useful ontological models for very complex domains. In addition, Protege-OWL was chosen for an ontology development tool because it is supported by METHONTOLOGY and is widely used because of its platform-independent characteristics. Based on the GSO development experience of the researchers, some issues relating to the METHONTOLOGY, OWL-DL, and Prot$\acute{e}$g$\acute{e}$-OWL were identified. We focused on presenting drawbacks of METHONTOLOGY and discussing how each weakness could be addressed. First, METHONTOLOGY insists that domain experts who do not have ontology construction experience can easily build ontologies. However, it is still difficult for these domain experts to develop a sophisticated ontology, especially if they have insufficient background knowledge related to the ontology. Second, METHONTOLOGY does not include a development stage called the "feasibility study." This pre-development stage helps developers ensure not only that a planned ontology is necessary and sufficiently valuable to begin an ontology building project, but also to determine whether the project will be successful. Third, METHONTOLOGY excludes an explanation on the use and integration of existing ontologies. If an additional stage for considering reuse is introduced, developers might share benefits of reuse. Fourth, METHONTOLOGY fails to address the importance of collaboration. This methodology needs to explain the allocation of specific tasks to different developer groups, and how to combine these tasks once specific given jobs are completed. Fifth, METHONTOLOGY fails to suggest the methods and techniques applied in the conceptualization stage sufficiently. Introducing methods of concept extraction from multiple informal sources or methods of identifying relations may enhance the quality of ontologies. Sixth, METHONTOLOGY does not provide an evaluation process to confirm whether WebODE perfectly transforms a conceptual ontology into a formal ontology. It also does not guarantee whether the outcomes of the conceptualization stage are completely reflected in the implementation stage. Seventh, METHONTOLOGY needs to add criteria for user evaluation of the actual use of the constructed ontology under user environments. Eighth, although METHONTOLOGY allows continual knowledge acquisition while working on the ontology development process, consistent updates can be difficult for developers. Ninth, METHONTOLOGY demands that developers complete various documents during the conceptualization stage; thus, it can be considered a heavy methodology. Adopting an agile methodology will result in reinforcing active communication among developers and reducing the burden of documentation completion. Finally, this study concludes with contributions and practical implications. No previous research has addressed issues related to METHONTOLOGY from empirical experiences; this study is an initial attempt. In addition, several lessons learned from the development experience are discussed. This study also affords some insights for ontology methodology researchers who want to design a more advanced ontology development methodology.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.1
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• pp.101-127
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• 2018

The systematic management of research data is vital because it increases research data's value for research reproduction, verification, and reusability. Standard metadata will play a key role in research data registration, management, and data extraction. Research data has various structural relationships, such as research, research data, data sets, and files, and associated with entities such as citations and research results. The study proposes an ontology model for research data management. It also suggests the application of ontology to NTIS. Previous studies, metadata standard analyses, and research data repository case studies were conducted.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.23-33
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• 2014

The development of the information retrieval field is evolving to the research field searching accurately for the information from thing finding rapidly a large amount of information. Personalization and the semantic web technology is a key technology. The automatic indexing technology about the web document and throughput go beyond the research stage and show up as the practical service. However, there is a lack of research on the document information retrieval field about the attached document type of except the web document. In this paper, we illustrate about the method in which it analyzed the text content of the unstructured documents prepared in the text, word, hwp form and it how to construction OWL ontology. To build TBox of the document ontology and the resources which can be obtained from the document is selected, and we implement with the system in order to utilize as the instant of the constructed document ontology. It is effectually usable in the information retrieval and document management system using the semantic technology of the correspondence document as the ontology automatic construction of this kind of the unstructured documents.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.269-282
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• 2007

We propose a personalized concept-based retrieval technique that uses domain ontology. Proposed system consist or representative concept extraction, user profile construction, and concept-based retrieval stages. First, we extract representative concept with using technique form contents and create the domain ontology. We compose user profile analysis that uses domain ontology for personalized concept-based retrieval. To verify the efficiency of the proposed technique, we perform experiment for Internet site in the engineering area. The results of experiment show that the proposed technique using the domain ontology and user profiles is more efficient than the existing techniques. Hence, the proposed concept-based retrieval technique can be expected to contribute to the development of an efficient personalized recommendation system or e-Commerce system.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.309-316
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• 2006

We propose a novel technique to categorize XML documents and extract a concept efficiently using domain ontology. First, we create domain ontology that use text mining technique and statistical technique. We propose a DScore technique to classify XML documents by using the structural characteristic of XML document. We also present TScore technique to extract a concept by comparing the association term set of domain ontology and the terms in the XML document. To verify the efficiency of the proposed technique, we perform experiment for 295 papers in the computer science area. The results of experiment show that the proposed technique using the structural information in the XML documents is more efficient than the existing technique. Especially, the TScore technique effectively extract the concept of documents although frequency of term is few. Hence, the proposed concept-based retrieval techniques can be expected to contribute to the development of an efficient ontology-based knowledge management system.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.221-225
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• 2009

Constructing an ontology using a mass corpus begins with an automatic semantic relation extraction. A general method regards words appearing between terms as patterns which are used to extract semantic relations. However, previous approaches consider only one sentence to extract a pattern, so they cannot extract semantic relations for terms in different sentences. This paper proposes a semantic relation extraction method using pairs of patterns sharing a term, where each pattern is extracted using one of the seed term pair satisfying the target relation. In our experiments, we achieved the accuracy 83.75% improving previous methods by 7.5% in is-${\alpha}$ relation and the accuracy 83.75% improved by 5% in part-of relation. We also present a possibility of improving the recall by the relative recall.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.111-120
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• 2015

Recently, self-adaptive system researches have been done to solve the problems occurred in the dynamic environment. Designing requirement in the self-adaptive system is necessary to recognize and solve the problem for the system, and if a developer reuses existing adaptation strategy to design the requirement, the designing time and cost would be reduced. Therefore, this paper proposes the system which extracts reusable adaptation strategy from the existing self-adaptive system. For the proposal, this paper conceptualizes the self-adaptation elements, defines the adaptation strategy ontology and target system ontology, and presents the process of extracting reusable strategy. This paper also implements proposed system and evaluates the reuse rate of the extracted strategy. As a result, the adaptation strategies extracted by proposed system are exactly operated, and the extraction method of proposed system shows higher reuse rate than a previous method.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.143-158
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• 2013

HTML5, new standard for web language, is being standardized corresponding to the development of web. Since several new semantic elements have been added into HTML5 standard, current Web Environment is becoming more and more semantic. In order to provide better user experience by using information extraction from HTML5 page, new HTML5 Elements should be mapped to a corresponding Ontology. In this research, we will focus on new semantic elements to build Ontology from HTML5 document. For this purpose, we will propose a methodology of Schema level mapping rule and instance mapping rule.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.19-41
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• 2008

Cue words and phrases of critical sentences, Paradigms knowing the critical information between sentences, Rules extracting the sentences contained critical information and producing the critical sentences were made to construct the critical abstract of scholar journals in the web environment. The ontology aided to accomplish above works were designed, to manage and operate the cue words and phrases in documents and the symptoms related to Purpose, Method, Result, and Conclusion sentences. The results of performance test remarked to improve the advancement of extraction and production rules and the reinforcement of ontology's relationship.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1136-1141
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• 2003

Due to the lack of digitally usable standards, it has been known to be difficult to handle the biological data. For example, the name of genes and proteins changes over time or has several synonyms indicating different entities. To cope with these problems, several communities, including the Gene Ontology Consortium and PubGene are making their efforts to move science toward the semantic web vision. Although some progress has been made, its expressivity is not sufficient for full-fledged ontological modeling and reasoning. This paper suggests a methodology for representing and extracting biological knowledge by using Web Ontology Language (OWL) as an extension of Resource Description Framework Schema (RDFS). Some benefits of our approach are: (1) to ensure extended sharing of biological meta data on the Web, and (2) to enrich additional expressivity and the semantics of RDFS+OWL.