• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.29-34
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• 2016

Many researchers have used cohort DB (database) to predict the occurrence of disease or to keep track of disease spread. Cohort DB is Big Data which has simply stored disease and health information as separated DB table sets. To measure the relations between health information, It is necessary to reconstruct cohort DB which follows research purpose. In this paper, XML descriptor, editor has been used to construct ontology-based Big Data cohort DB. Also, we have developed ontology based cohort DB search system to check results of relations between health information. XML editor has used 7 layered Ontology development 101 and OWL API to change cohort DB into ontology-based. Ontology-based cohort DB system can measure the relation of disease and health information and can be used effectively when semantic relations are found. We have developed ontology-based cohort DB search system which can measure the relations between disease and health information. And it is very effective when searched results are semantic relations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.11-20
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• 2010

Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

• Asia pacific journal of information systems
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• v.16 no.4
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• pp.151-178
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• 2006

The objective of this research is to develop a formal framework and methodology to facilitate real-time data integration, thus enabling semantic interoperability among distributed and heterogeneous information systems. The proposed approach is based on the concepts of "ontology" and "semantic mediators." An ontology is developed and used to capture the intension (including structure, integrity rules and meta-properties) of the database schema. We also develop the agent communication protocol for semantic reconciliation, which is based on the theory of speech acts and agent communication language. This protocol is used by a set of semantic mediators, which automatically detect and resolve various semantic conflicts at the data- and schema-levels by referring to the ontology. A mediation-based query processing technique is developed to provide uniform and integrated access to the multiple heterogeneous information sources. Prototype tools are being implemented to provide proof of concept for this work.

• 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 the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.146-157
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• 2009

In order to implement ontology data searching system, this paper uses some methods that effectively analyse searching options/key words with event process model and design pattern. I will propose some techniques on object-oriented process model that should improve reusability of system and reusability of ontology data which users can obtain more precise searching results. This paper shows that ontology-based data searching can assure users of the precision of searching results. Therefore, ontology-based data searching system on object-oriented design pattern is expected to show high stability and reliability, enhance reusability and scalability of modules and softwares and provide reliable data searching results to users.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.15-23
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• 2010

This paper presents a method of constructing a large interlinked ontology network for the Web of Data through the mapping among typical ontologies. When an ontology is open to the public, and more easily shared and used by people, its value is increased more and more. By linking CoreOnto, an IT core ontology constructed in Korea, to the worldwide ontology network, CoreOnto can be open to abroad and enhanced its usability. YAGO is an ontology constructed by combining category information of Wikipedia and taxonomy of WordNet, and used as the backbone of DBpedia, an ontology constructed by analyzing Wikipedia structure. So a mapping method is suggested by linking CoreOnto to YAGO and DBpedia through the synset of WordNet.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.117-127
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• 2007

As the value of the multimedia data is getting high, the study on the semantic recognition and retrieval about the multimedia information is strongly demanded. In this paper, we build the motion ontology and adopt it for representing the meaning of the moving objects in video data. By referencing the WordNet structure, we extend its semantic meaning based on the reclassification of motion verbs, which are used to represent the semantic meaning of moving objects. The represented information is receded in OWL/RDF(S). Here, we could expect the 'Is-A' and 'Equivalent' reasoning of the data as we use the ontologies. And the semantic representation about the moving objects is possible through the video annotation using ontology. And we tested the accuracy of the system comparing with the key-word based system. As a result, we could get the approximately 10% improvement of the system performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.157-162
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• 2008

This paper presents a learning method of tagging ontology using large tagging data such as a folksonomy, which stands for classification structure informally created by the people. There is no common agreement about the semantics of a tagging, and most social web sites internally use different methods to represent tagging information, obstructing interoperability between sites and the automated processing by software agents. To solve this problem, we need a tagging ontology, defined by analyzing intrinsic attributes of a tagging. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tagging ontology is also suggested as an applying field.

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.229-235
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• 2001

As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, exchanging them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step to overcome the current difficulties on sharing product data. In this paper, we utilize the ontology concept in order to facilitate information search far product data in the internet environment. A prototype of search system implemented using the ontology for automobile product data is presented.