• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.191-196
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• 2003

The Semantic web service is able to intelligently discover, execute, composite and monitor the Web Service. It constructs the ontology on Web Service and describes the Semantic Markup in the machine-readable form. The currently developing technologies of the Semantic Web Service discovery are DAML-S matchmaker in Carnegie Mellon University, Process Handbook in MIT and etc. In this paper, we propose the ontology language based on Topic Maps that supports the benefits and solves the problems of the Semantic Web Service discovery technologies .

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.1022-1031
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• 2009

In this paper, we propose a researcher modeling technique based on ontology and construct social network for researchers using diverse relational properties. User ontology schema is created by extending the existing HR-XML model for a researcher model. User ontology schema and instance are created by OWL. We compose social network model for efficient cooperation between researchers using static relational properties such as educational background and dynamic relational properties such as co-authors and co-workers, etc. Closeness has direction because researcher network is differently configured by the researchers. We define inferencing rules using SWRL and inference ontology rules using racer inference machine to compose direct relationships between researchers. The proposed model for researchers can be applied to the cooperation model for researchers by retrieving common expert group dynamically.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.385-389
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• 2009

As a new community forming environment, the blog platform enables sharing of the resources in blogosphere through active information exchange. Many researches have been performed to recommend appropriate resources to users from vast amounts of blog resources. As one of the solutions OSEM defines the knowledge base in the blogosphere with ontology for effectively modeling it. In this paper, we propose a technique of converting the knowledge base into the OWL ontology for sharing it on the semantic web environment. An inference method is then applied to the OWL ontology for recommending interest blog communities. For this aim, a mapping method is offered and then SWRL inference and SPARQL query based on the ontology are employed to extract interest blog communities.

• Journal of Information Technology and Architecture
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• v.10 no.2
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• pp.263-271
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• 2013

In this paper, we propose a new XMDR-based data model to efficiently manage ontology schema structured in OWL format. The proposed model would be better equipped to manage the relationship between concepts, which is a problematic area in the existing MDR model. Moreover, we present an algorithm to manage ontology schema in the database. To demonstrate the effectiveness of the proposed algorithm, experiments were conducted to recreate OWL documents for the various expressive types of OWL ontology schema that are stored in the database. These experimental results demonstrated that the proposed model effectively managed the various types of OWL ontology schema.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.4
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• pp.231-257
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• 2018

This paper aims to suggest a facet-based ontology model that can help sort and access records of dispersed families to address these problems. The facet systematically defines the categories of target concepts, which can create diverse and multiple access points. Using the top-down and bottom-up approaches, the facets, which consist of five upper classes and 18 lower classes, were derived for the records of dispersed families. The proposed ontology model was evaluated by real users. The results show that, overall, the ontology is complete and relevant in terms of access points, availability of context information of the records, and description elements for search and use of the records on dispersed families.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.470-471
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• 2013

Accuracy of mappings is the key for achieving true interoperability among different healthcare systems. The initial step towards interoperable healthcare systems is compliancy with healthcare standards (HL7, openEHR, CEN 13606). Ontologies for these standards are developed that require ontology matching to generate generalized ontology mappings. Organizations conform to specific concepts of different standards based on their requirements. This step is called as conformance claims and is based on Personalized-Detailed Clinical Model. It invalidates some of the generalized mappings because of non-conformed concepts and leads to the necessity of the proposed technique of customized ontology mappings. These customized ontology mappings compliment the generalized ontology mapping to increase the level of accuracy of mappings and thus achieving data interoperability. The proposed system ensures quality of care to patients by timely delivery of healthcare information.

• Journal of KIISE
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• v.43 no.5
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• pp.553-561
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• 2016

Several machine learning techniques are able to automatically populate ontology data from web sources. Also the interest for large scale ontology reasoning is increasing. However, there is a problem leading to the speculative result to imply uncertainties. Hence, there is a need to consider the reliability problems of various data obtained from the web. Currently, large scale ontology reasoning methods based on the trust value is required because the inference-based reliability of quantitative ontology is insufficient. In this study, we proposed a large scale OWL Horst reasoning method based on a confidence value using spark, a distributed in-memory framework. It describes a method for integrating the confidence value of duplicated data. In addition, it explains a distributed parallel heuristic algorithm to solve the problem of degrading the performance of the inference. In order to evaluate the performance of reasoning methods based on the confidence value, the experiment was conducted using LUBM3000. The experiment results showed that our approach could perform reasoning twice faster than existing reasoning systems like WebPIE.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.562-571
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• 2008

For the purpose of building domain ontology, this paper proposes a methodology for building core ontology first, and then enriching the core ontology with the concepts and relations in the domain thesaurus. First, the top-level concept taxonomy of the core ontology is built using domain dictionary and general domain thesaurus. Then, the concepts of the domain thesaurus are classified into top-level concepts in the core ontology, and relations between broader terms (BT) - narrower terms (NT) and related terms (RT) are classified into semantic relations defined for the core ontology. To classify concepts, a two-step approach is adopted, in which a frequency-based approach is complemented with a similarity-based approach. To classify relations, two techniques are applied: (i) for the case of insufficient training data, a rule-based module is for identifying isa relation out of non-isa ones; a pattern-based approach is for classifying non-taxonomic semantic relations from non-isa. (ii) For the case of sufficient training data, a maximum-entropy model is adopted in the feature-based classification, where k-NN approach is for noisy filtering of training data. A series of experiments show that performances of the proposed systems are quite promising and comparable to judgments by human experts.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.146-151
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• 2010

For an application of ontology, query processing is mandatory field for efficient information search in the ontology. Other query processing systems tend to analyze only facts and to simply provide structural information for users. In fact, the systems do not have big difference with database systems or text based information processing systems. Therefore, in this research, the method which can provide the inferred information based on axioms is suggested in order to maximize reusability of ontology.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.247-256
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• 2008

This research is to develop product retrieval system through simplified communication by applying intelligent agent technology based on automatically created domain ontology to present solution on problems with e-commerce system which searches in the web documents with a simple keyword. Ontology development extracts representative term based on classification information of international product classification code(UNSPSC) and jewelry websites that is applied to analogy relationship thesaurus to establish standardized ontology. The intelligent agent technology is applied to retrieval stage to support efficiency of information collection for users by designing and developing e-commerce system supported with semantic web. Moreover, it designs user profile to personalized search environment and provide personalized retrieval agent and retrieval environment with inference function to make available with fast information collection and accurate information search.