• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.13-21
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• 2001

This paper studies on Multiple Ontology to share and reuse know1edge stored in every system under the Distributed Web Environment using idle resource connected the Internet. Multiple Ontology is to convert to be able know1edge sharing between ontologies constructed by one and the other. This study focuses on as follows; To compose the Distributed Web Ontology multiple system, Construction Method of the Distributed Web Environment and Composition of Multiple Ontology for Know1edge sharing and reuse. System Composed by using the jini technology has constructed extension of heterogeneous systems and effective web computing environment. Also, through 'distribution operation, practical know1edge exchange among Multiple Ontologies under the Distributed Web Environment has been processed excellently.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.19-30
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• 2008

Semantic heterogeneity should be overcome to support automated information sharing process between information systems in ontology-based distributed environments. To do so, traditional approaches have been based on explicit mapping between ontologies from human experts of the domain. However, the manual tasks are very expensive, so that it is difficult to obtain ontology mappings between all possible pairs of information systems. Thereby, in this paper, we propose a system to make the existing mapping information sharable and exchangeable. It means that the proposed system can collect the existing mapping information and aggregate them. Consequently, we can estimate the ontology mappings in an indirect manner. In particular, this paper focuses on query propagation on the distributed networks. Once we have the indirect mapping between systems, the queries can be efficiently transformed to automatically exchange knowledge between heterogeneous information systems.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.133-141
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• 2008

Social Web is turning current Web into social platform for knowing people and sharing information. This paper takes major social tagging systems as examples, namely delicious, flickr and youtube, to analyze the social phenomena in the Social Web in order to identify the way of mediating and linking social data. A simple Tag Ontology (TO) is proposed to integrate different social tagging data and mediate and link with other related social metadata. 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 tag ontology is also suggested as an applying field.

• 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.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.65-67
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• 2010

위치기반서비스(LBS)는 사용자의 위치를 기반으로 다양한 정보제공 서비스를 하고 있다. 최근 연구에서는 단순한 정보제공이 아닌 사용자의 상황인식(Context-Aware)을 통하여 사용자에게 적합한 정보를 제공해주는 지능화된 서비스를 제공하고 있다. 하지만 현재 연구들은 사용자의 기본정보와 선호도정보를 이용한 단일기준 추론을 통하여 사용자에게 정보를 제공해주고 있으며, 이것은 사용자의 다양한 기준의 의사결정을 반영하지 못하는 한계점이 있다. 이러한 한계점을 극복하기 위하여 본 연구에서는 사용자의 정보, 선호도, 공간지리선호도 정보 Ontology를 구축하고, 의사 결정 기준에 가중치를 부여하는 Cost Value Ontology를 구축하여, 다 기준 의사추론을 통해 사용자에게 적절한 추천 결과가 도출되는 Ontology 추론시스템을 제안한다. 사용자들의 개인적인 특성 지식과 공간지리 선호도 지식을 구축할 수 있으며, 이러한 특성으로 구축된 지식 기반 하에 입력된 사용자 정보와 추론을 통하여 이 시스템을 통해 사용자의 선호도 Ontology를 구축할 수 있으며 이를 이용한 추론을 통하여 사용자의 현재상황에 적합한 결과를 도출함을 보였다.

• Korean Journal of Computational Design and Engineering
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• v.19 no.1
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• pp.29-40
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• 2014

Conceptual Modeling is the process of abstracting a model from a real or proposed system. It is probably the most important aspect of a simulation study. Relate works show that the elementary developers devoted little time to understanding how the systems actually worked, namely they didn't build appropriate conceptual model. Thus, the result of simulation is inconsistent because it depends on developer's competence. Although many researchers suggested various techniques enabling developer to build conceptual model, there were several limitations. In this study, to overcome the limitations of existing techniques, we proposed COMBINE-DES (COnceptual Model BuildINg framEwork using ontology for Discrete Event Simulation). The COM-BINE-DES supports expediting the conceptual modeling with Solution ontology generated by Domain ontology and Simulation ontology. Moreover, it provides consistent simulation result regardless of repeated modeling.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.375-378
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• 2016

The difficulty of "information sharing", "information reusing" issues happening in Wireless Sensor Network is due to the heterogeneity of the application environment, data processing, communication protocol etc. Based on the introduction of the Ontology theory, though analyzing the sensor characteristic a general type of sensor ontology contains the definition of concept, frame structure and OWL design was proposed from the standpoint of sensor observation. The paper expounded a system framework of the domain ontology through the expansion of knowledge base on the general sensor could achieve the information sharing and reuse by semantic communication between the general sensor ontology and user. The research of this method would bring new idea to the semantic sensor network construction.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.491-500
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• 2004

This paper presents an ontology construction method using various computational language resources, and an ontology-based word sense disambiguation method. In order to acquire a reasonably practical ontology the Kadokawa thesaurus is extended by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. To apply the ontology to disambiguate word senses, we apply the previously-secured dictionary information to select the correct senses of some ambiguous words with high precision, and then use the ontology to disambiguate the remaining ambiguous words. The mutual information between concepts in the ontology was calculated before using the ontology as knowledge for disambiguating word senses. If mutual information is regarded as a weight between ontology concepts, the ontology can be treated as a graph with weighted edges, and then we locate the weighted path from one concept to the other concept. In our practical machine translation system, our word sense disambiguation method achieved a 9% improvement over methods which do not use ontology for Korean translation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.591-593
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• 2010

The Ontology is the concept of human beings in any sense to classify things as departure from the classification based on the meaning at the prensent situation and concepts as the object of the Ontology. also, the technology is shared the conceptualization in a formal ontology as a meaning to give a clear description to the conceptual engineering in the ontology. Specialized multimedia broadcasting of TV-Anytime standard and multimedia representation of the overall standard of the MPEG-7 based on the concept of broadcasting multimedia presentations that can be used to develop an ontology who is required. In this paper, in TV-Anytime and MPEG-7 multimedia standard for broadcasting multimedia contents based on standards developed for the ontology, an ontology language for expressing OWL (Web Ontology Language) and RDF (Resource Description Framework) and the broadcast contents using To represent metadata of the system who has been developed.