• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.253-269
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• 2007

The purpose of this study is modeling a user-friendly Korean-Japanese thesaurus for internet circumstances. The methodology had two steps: first, the problems were analyzed when multilingual thesaurus is constructed, with review of various multilingual thesauri and interview with multilingual thesaurus constructor in Korea and Japan. Second, collaborative tags were analyzed to differentiate cultural/linguistic background from word usage pattern. As a result, searching thesaurus model was suggested and applied to develop a user-friendly Korean-Japanese thesaurus.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.27-47
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• 2004

In this study, the experiment was made to transform the relationship among terms in a thesaurus to ontology language as search tools for multilingual text. As a result, the equivalent relationship in the thesaurus can be expressed by different ways in the ontology, such as equivalentClass, equivalentProperty, sameAS, and so on. On the other hand, the associative relationship can be represented by ObjectProperty, DatatypeProperty, and inverseOf. For this test, first of all, the descriptors assigned by AAT and the descriptors from bilingual thesaurus by ICCD were translated into Korean. Then, the facet was used for conceptual equivalence among terms from different languages. The result of the study showed that using rdf:Property in ontology was the most effective way of transforming multilingual thesaurus into ontology.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.1-13
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• 2004

This paper presents a method for the multilingual product retrieval agent through XML and the semantic networks in e-commerce. Retrieval for products is an important process, since it represents interfaces of the customer contact to the e-commerce. Keyword-based retrieval is efficient as long as the product information is structured and organized. But when the product information is expressed across many online shopping malls, especially when it is expressed in different languages with cultural backgrounds, buyers' product retrieval needs language translation with ambiguities resolved in a specific context. This paper presents a RDF modeling case that resolves semantic problems in the representation of product information and across the boundaries of language domains. With adoption of UNSPSC code system, this paper designs and implements an architecture for the multilingual product retrieval agents. The architecture is based on the central repository model of product catalog management with distributed updating processes. It also includes the perspectives of buyers and suppliers. And the consistency and version management of product information are controlled by UNSPSC code system. The multilingual product names are resolved by semantic networks, thesaurus and ontology dictionary for product names.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.135-161
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• 2002

This study presents a multilingual integrated ontological approach that enables linking classification systems. thesauri. and terminology databases in science and technology for more effective indexing and information retrieval online. In this integrated system, we designed a thesaurus model with concept as a unit and designated essential data elements for a terminology database on the basis of ISO 12620 standard. The classification system for science and technology adopted in this study provides subject access channels from other existing classification systems through its mapping table. A prototype system was implemented with the field of nuclear energy as an application area.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.25-43
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• 2009

The purpose of this study is to suggest how the classic thesaurus structure of terms and links can be mined and updated from Wikipedia encyclopedia, which is the best practice of collective intelligence. In a comparison with ASIS&T thesaurus, it was found that Wikipedia contains a substantial coverage of domain-specific concepts and semantic relations. Furthermore, it was resulted that the structural characteristics of Wikipedia, such as redirects, categories, and mutual links are suitable to extract semantic relationships of thesaurus. It is needed to apply to update various thesauri, including multilingual thesaurus, in order to generalize the results of this research.

• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.5-10
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• 2001

둘 이상의 언어를 포함하고, 그 중 참조하는 언어를 중심으로 용어관계를 표시할 수 있는 다국어 시소러스의 개념구조에 대하여 논하였다. 아울러, 우리말을 기준어로 삼고, 기본요건, 구조화, 용어관계, 동형이의어, 표시방법, 배열 등에 대한 예시와 함께 다국어 시소러스의 설계방안을 제시하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.53-62
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• 2008

Cross-lingual text retrieval(CLTR) is the information retrieval in which a user tries to search a set of documents written in one language for a query another language. This thesis proposes a CLTR system based on fuzzy multilingual thesaurus to handle a partial matching between terms of two different languages. The proposed CLTR system uses a fuzzy term matrix defined in our thesis to perform the information retrieval effectively. In the defined fuzzy term matrix, all relation degrees between terms are inferred from using the transitive closure algorithm to reflect all implicit links between terms into processing of the information retrieval. With this framework, the CLTR system proposed in our thesis enhances the retrieval effectiveness because it is able to emulate a human expert's decision making well in CLTR.

• Journal of Information Management
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• v.26 no.2
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• pp.61-79
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• 1995

The purpose of this paper is to investigate search efficiency of controlled vocabulary versus uncontrolled vocabulary subject access in online catalog systems. The question of the effectiveness of controlled versus uncontrolled vocabulary in information retrieval has been raised in many literatures. A debate continues in the Library and Information Science Professions over the relative merit, appropriateness, and efficiency of uncontrolled vocabulary subject access in online catalog systems. Actually users used to combine uncontrolled vocabulary subject searching with controlled vocabulary subject searching. But the success of user's subject search depends on his choice of search terms. Also the technical developments that facilitate cooperation among information services in general make it increasingly possible for such cooperation to take place on an international level. In this study, several common types of vocabularies on online catalog systems are described and compared, especially usages of vocabularies in multilingual environment are analyzed.

• Korean Journal of Oriental Medicine
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• v.12 no.3 s.18
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• pp.1-15
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• 2006

For the recent several years, there has been much interest in lexical semantic network. However, it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic word clustering systems, which are called system A and system B respectively. 68,455,856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3,656 '-ha' verbs. The target data is the 'multilingual Word Net-CoreNet'.When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A, 45.3%.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.175-190
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• 2006

For the recent several years, there has been much interest in lexical semantic network However it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic vol·d clustering systems, which are called system A and system B respectively. 68.455.856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3.656 '-ha' verbs. The target data is the 'multilingual Word Net-CoroNet'. When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A. 45.3%.