• The Journal of Society for e-Business Studies
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• v.10 no.4
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• pp.19-33
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• 2005

In this study, we propose a methodology of mating it easy to integrate the heterogeneous and distributed information of e-Business environments with the semantic web components , knowledge representation, ontology and agents. It is based on a collaborative interoperable environment, which should be constructed by meta-modeling and employing agents , and the syntactic/semantic integration. We adopt OWL(Web Ontology Language) to specify ontology in a layered architecture for each agent to use, which is based on the IRDS (Information Resource Dictionary Standard) framework. And we give an illustrative example using the terms from PSL(Process Specification Language)-ontology. By defining, managing and sharing resources and business-processes on the proposed framework, it could be possible to get rid of the cause of redundancy and inconsistency.

• Proceedings of the IEEK Conference
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• summer
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• pp.376-381
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• 2004

The Semantic Web is an extension of the current Web in which information is given formal and explicit meaning. The Semantic Web enables computer programs to understand information contents and thus facilitates more efficient discovery, automation, integration and sharing of data. To create Semantic Web contents one needs appropriate tools. In this paper, we describe such a toolkit we have constructed. The most important feature of the toolkit is that it makes use of information extraction techniques for automatically annotating web page contents. Experiments with a real life application show promising results and demonstrate the usefulness of the toolkit.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.129-136
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• 2006

Information Retrieval System aims towards providing fast and accurate information to users. However, current search systems are based on plain svntactic analysis which makes it difficult for the user to find the exact required information. This paper proposes the SW-IRS (Semantic Web-based Information Retrieval System) using an Ontology Server. The proposed system is purposed to maximize efficiency and accuracy of information retrieval of unstructured and semi-structured documents by using an agent-based automatic classification technology and semantic web based information retrieval methods. For interoperability and easy integration, RDF based repository system is supported, and the newly developed ranking algorithm was applied to rank search results and provide more accurate and reliable information. Finally, a new ranking algorithm is suggested to be used to evaluate performance and verify the efficiency and accuracy of the proposed retrieval system.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.189-194
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• 2013

Semantic Web is what supports a search, data integration, and automated web service by developing technology of giving help so that a computer can understand information a little more on the web. As amount of information gets growing and diverse, there is a problem of offering by efficiently extracting and processing only information proper for users' demand. Semantic Web isn't what is distinguished completely from the existing web. It gives a meaning, which was well defined, to information of being inserted on web by expanding the current web. Through this, a computer and a person come to perform work cooperatively. To implement Semantic Web, the limit of HTML needs to be overcome. The existing access authorization has not taken information and semantics into account due to the limitations of HTML. It is difficult to expand or integrate many relevant documents by using HTML. Program or software agent, not a person, cannot extract a meaning of document automatically. This study suggests a method of Access Authorization Policy Management that is in the Semantic Web configuration. Accordingly, the policy, which was designed in this study, improved the authorization process more than the existing method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.579-587
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• 2008

In collaborative environment, since each agent generally uses different words for the same meaning, there is an obstacle for information sharing. In collaborative product development environment, each agent has different words for representing same product information. As a result, it is hard to share product information in this situation. For solving this problem, semantic-based product information is needed. In this paper, a ontology-based semantic searching system which is able to interact with legacy PDM systems is proposed for product information sharing in collaborative environment Product ontology is represented with OWL format, and the product ontology is processed by Pellet reasoning engine for semantic searching. The system is implemented as a web service which can be integrated with other systems. This paper also introduces the approach with which a PDM system provides a function of semantic search with this search system.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.57-64
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• 2003

Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged. methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.101-119
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• 2003

Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged, methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.247-260
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• 2003

To share and standardize information, especially in the database environments, MDR (Metadata Registry) can be used to integrate various heterogeneous databases within a particular domain. But due to the discrepancies of data element representation between organizations, global information integration is not so easy. And users who are searching integrated information on the Web have limitation to obtain schema information for the underlying source databases. To solve those problems, in this paper, we present a 3-layered Information Integration System (LI2S) based on MDRs and Ontology. The purpose of proposed architecture is to define information integration model, which combine both of the nature of MDRs standard specification and functionality of ontology for the concept and relation. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent information integration architecture. Ontology is used as for a role of semantic network from which it extracts concept from the user query and the establishment of relationship between MDRs for the data element. (MDR and Knowledge Base are used as for the solution of discrepancies of data element representation between MDRs. Based on this architectural concept, LI2S was designed and implemented.

• The Journal of Society for e-Business Studies
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• v.8 no.2
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• pp.63-76
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• 2003

The fundamental technology to the b2b e-commerce framework is Registry. Although Registries have developed, it is yet difficult to apply in actual e-business . That is, the e-business information was stored in physically and/or logically distributed and heterogeneous Registries. And Registry uses the keyword-based search to discovery the information stored. But, the keyword-based search technology can't provide the discovery the business information necessary for parties and trading partners. As spreading the understand of this problem, it requires the technologies for the integration of distributed and various Registries and the systematic definition and intelligent discovery of the e-business information. In this paper we propose the architecture of intelligent and integrated e-business registry system for solving these problems . This system composed of the Registry Integration Query Manager for integrating various registries and the Intelligent Registry Agent providing the systematic organization and discovery of e-business information.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.