• Korean Journal of Computational Design and Engineering
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• v.9 no.3
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• pp.192-202
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• 2004

This paper introduces an approach to semantic mapping using Product ontology for CPC environment. In CPC environment, it is necessary that the participants in a product life cycle should share the same understanding about the semantic of product terms. For example, they should know that although 'COMPONENT' and 'ITEM' are different word-expressions, they could have the same meaning. In order to handle such terms in the information system, it is desirable that the system automatically recognizes that the terms have the same semantics. Serving this purpose, we described an ontology design methodology using first order logic, knowledge interchange format, and knowledge engineering process. In our approach, we investigated domain knowledge of the Bill Of Material, and then designed Product ontology of it. Based on the ontology, we described syntactic translation, semantic translation, and semantic mapping procedure with an example.

• Journal of Korea Technology Innovation Society
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• v.8 no.2
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• pp.605-622
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• 2005

Because, next generation web, semantic web consists of documents with semantic information, it enables computer interpret the contents of the documents, so that the information retrieval, interpretation and integration can be automated. The web documents with the semantic information may be made in ontology. In this paper, collaborative approach among the ontology design techniques is more excellent than the other techniques because it design the ontology through continuous evaluations and modification in terms of multiple views. So, we propose the process of designing and implementing the ontology for specific domain, which is Yeomigi tour place. Delphi technique, that is a kind of collaborative approach, is used when the ontology is designed.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.523-530
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• 2014

Ontology alignment is the way to share and reuse of ontology knowledge. Because of the ambiguity of concept, most ontology alignment systems combine a set of various measures and complete enumeration to provide the satisfactory result. However, calculating process becomes more complex and required time increases exponentially since the number of concept increases, more errors can appear at the same time. Lately the focus is on meta-matching using the heuristic algorithm. Existing meta-matching system tune extra parameter and it causes complex calculating, as a consequence, the results in the various data of specific domain are not good performed. In this paper, we propose a high performance algorithm by using DCS that can solve ontology alignment through simple process. It provides an efficient search strategy according to distribution of Levy Flight. In order to evaluate the approach, benchmark data from the OAEI 2012 is employed. Through the comparison of the quality of the alignments which uses DCS with state of the art ontology matching systems.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1321-1322
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.733-734
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• 2009

• Journal of Digital Convergence
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• v.10 no.9
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• pp.311-317
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• 2012

This study suggested ontology design to help heart-wounded users to be healed from their wounded heart. The ontology development framework which this article applied or adapted was mainly based on 9-step ontology development frameworks suggested by E. King and Reinold. The procedures of this study were collections and classification of related technical terms following the definitions of ontology and ontology users. In case added technical terms in the process of the study was founded, the definitions of their synonyms was utilized to complete ontology design. In addition, this article presented possibilities of offering new information by combining various characteristics of wounded heart, activating the expansion of ontology conception.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.153-160
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• 2009

As size of ontology has been increased more and more, the descriptions in the ontologies become more complicated, Therefore finding and modifying unsatisfiable concepts is hard work in ontology construction process, Minerva is an ontology reasoner which detects unsatisfiable concepts automatically and infers subsumption relation between concepts in ontology, Most description logic based ontology reasoners (including Minerva) work using tableaux algorithm, Because tableaux algorithm is very costly, ontology reasoners need various optimization methods, In this paper, we propose optimizing methods to reduce execution time of tableaux algorithm based ontology reasoner. Proposed methods were applied to Minerva which was developed as preceding study result. In consequence the new version Minerva shows high performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.61-70
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• 2008

This paper describes case studies on workflow impact analyze with an enterprise ontology (EO). We build the EO with an ontology editor $Prot{\acute{e}}g{\acute{e}}$ and integrate concepts of enterprise architecture and a process model into it to expand the EO. We use the expanded EO and Prolog query rules to analysis workflow dependency relations from the perspectives of routing, data and role. Through this, we analyze impact of changes in workflow process. Moreover, we have found the effectiveness of the EO and $Prot{\acute{e}}g{\acute{e}}$ in modeling business management and, in particular, workflow representation and management.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.