• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.155-175
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• 2003

The purpose of the study was to construct a system based on the semantic web environment's ontology by utilizing the ontology schema derived from the facet-type Art and Architecture Thesaurus(AAT). The aforementioned ontology schema is based on the Web Ontology Language(OWL), which is being widely considered the standard ontology language for the W3C-centered semantic web environment. Also, the concepts were limited to terms within AAT'S Furniture Facet, and the system was tested using the Chair concept, which is a lower-level facet that has a diverse conceptual relationship and broad vocabulary base. The ontology system is capable of searching for concepts, while controlling the search results by always providing a 'Preferred term' for synonymous terms. In addition, the system provides the user with first, a relationship between the terms centered around the inquiry, and second, related terms along with their classification properties. Also, the system is presented as and application example of the ontology system that constructs a information system that intakes an Instance value and reproduces it into a RDF file. During this process, utilization of multiple ontologies was introduced, and the stored Instance value's meta-data elements were used.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.575-578
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• 2002

In this study, it enabled to perform keyword search on Geographic Information Systems (GIS) more flexibly by taking in the concept of geographic thesaurus in order to make the keyword search that was more efficiently. The search procedure depends on the history when user information is included. This study provides a system for keyword searching as well as check the validity of the system. Furthermore, by establishing this reference method, the search that took in the query of a user flexibly is attained rather than a chosen type reference system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.103-109
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• 2009

We build the web document recommending agent system which offers a certain amount of web documents to each user by monitoring and learning the user's action of web browsing. We also propose a method of query expansion using the Korean thesaurus. The queries to search for new web documents generate a candidate set using the Korean thesaurus. We extract the words which are mostly correlated with the queries, among the words in the candidate set, by using TF-IDF and mutual information. Then, we expand the query. If we adopt the system of query expansion, we can recommend a lot of web documents which have potential interests to users. We thus conclude that the system of query expansion is more effective than a base system of recommending web-documents to users.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.278-288
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• 2002

This paper presents a design and implementation of fuzzy retrieval system that could support an associated learning in problem banks. It tries to retrieve some of the problems conceptually related to specific semantics described by user's queries. In particular, the problem retrieval system employs a fuzzy thesaurus which represents relationships between domain dependent vocabularies as fuzzy degrees. It would keep track of characteristics of the associated learning, which should guarantee high recall and acceptable precision for retrieval effectiveness. That is, since the thesaurus could make a vocabulary mismatch problem resolved among query terms and document index terms, this retrieval system could take a chance to effectively support user's associated teaming. Finally, we have evaluated whether the fuzzy retrieval system is appropriate for the associated teaming or not, by means of its precision and recall rate point of view.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.49-59
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• 2007

This paper is about an system which can perform automatic semantic annotation to actualize "Semantic Web." Since it is impossible to tag numerous documents manually in the web, it is necessary to gather large Korean web documents as training data, and extract features by using natural language techniques and a thesaurus. After doing these, we constructed concept classifiers through the SVM (support vector machine) teaming algorithm. According to the characteristics of Korean language, morphological analysis and syntax analysis were used in this system to extract feature information. Based on these analyses, the concept code is mapped with Kadokawa thesaurus, which made it possible to map similar words and phrase to one concept code, to make training vectors. This contributed to rise the recall of our system. Results of the experiment show the system has a some possibility of semantic annotation.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.7-20
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• 1998

With our economic development and increment and increment of GNP, the number of autos has incremented. But lacking in mind for traffic safety and traffic order, many traffic accidents have occurred. So the purpose of development of traffic safety education system based on web is to advertise the importance and the need of traffic order and safety education and protect walkers and drivers from traffic accidents. The Contents and Scopes of Study Development are as follows. There are input of text, image and moving image data for traffic safety education, establishment of hierarchical relation for traffic safety education, relation analysis between traffic safety education information and design of hyper link structure between them, thesaurus implementation for traffic safety education system, design and implementation of information retrieval engine based on thesaurus, design and implementation of database schema for traffic safety education and GUI implementation for user.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.177-183
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• 2008

This paper aims to offer a solution based on intelligent document classification to create a user-centric information retrieval system allowing user-centric linguistic expression. So, structures expressing user intention and fine document classifying process using EBL, similarity, knowledge base, user intention, are proposed. To overcome the problem requiring huge and exact semantic information, a hybrid process is designed integrating keyword, thesaurus, probability and user intention information. User intention tree hierarchy is build and a method of extracting group intention between key words and user intentions is proposed. These structures and processes are implemented in HDCI(Hybrid Document Classification with Intention) system. HDCI consists of analyzing user intention and classifying web documents stages. Classifying stage is composed of knowledge base process, similarity process and hybrid coordinating process. With the help of user intention related structures and hybrid coordinating process, HDCI can efficiently categorize web documents in according to user's complex linguistic expression with small priori information.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.368-371
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• 2003

This paper constructed component retrieval system for reusability of component. Constructed by thesaurus that use inheritance relation of class for component retrieval, and did so that component retrieval that use Queries may be available. Also, the retrieval result did to become faster retrieval about queries as that show by priority. Retrieved components made efficient component reusability to be possible as that support source code, component information, class diagram etc.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.829-840
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• 2005

Word Sense Disambiguation(WSD) is one of the most difficult problem in Korean information processing. We propose a WSD model with the capability to filter semantic information using the specific characteristics in dictionary dictions, and nth added information, useful to sense determination, such as statistical, distance and case information. we propose a model, which can resolve the issues resulting from the scarcity of semantic information data based on the word hierarchy system (thesaurus) developed by Ulsan University's UOU Word Intelligent Network, a dictionary-based toxicological database. Among the WSD models elaborated by this study, the one using statistical information, distance and case information along with the thesaurus (hereinafter referred to as 'SDJ-X model') performed the best. In an experiment conducted on the sense-tagged corpus consisting of 1,500,000 eojeols, provided by the Sejong project, the SDJ-X model recorded improvements over the maximum frequency word sense determination (maximum frequency determination, MFC, accuracy baseline) of $18.87\%$ ($21.73\%$ for nouns and inter-eojeot distance weights by $10.49\%$ ($8.84\%$ for nouns, $11.51\%$ for verbs). Finally, the accuracy level of the SDJ-X model was higher than that recorded by the model using only statistical information, distance and case information, without the thesaurus by a margin of $6.12\%$ ($5.29\%$ for nouns, $6.64\%$ for verbs).

• Journal of Korean Society of Archives and Records Management
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• v.8 no.1
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• pp.189-210
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• 2008

Some issues and solutions considered for the various situations that we faced in the process of developing guidelines of thesaurus construction are described in this paper. There were many proper names and proper nouns among the terms considered in the process. The thesaurus needed to include a function of an authority file. Preferred terms were selected based on what the university's official records would use. The scope of the proper names for inclusion was the people who held official positions in the university and the people who were the subject of the materials. However, when the system allows synthesized retrieval of the field of creator and donor, inclusion of too many names were considered unnecessary.