• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.45-67
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• 2015

The purpose of this study is to analyse the semantic relations of terms in STNet, a structured terminology dictionary based on author keywords of humanities, social sciences, and art and sport in the Korea Citation Index (KCI) and to describe the procedure for optimizing the relation types and specifying the name of relationships. The results indicate that four logical criteria, such as creating new names for relationships or limitation of typing the relationship by the appearance frequency of same type, consideration of direction of relationship, reflection to accept the existing name of relationships, are required for the optimization of the typing and naming the relationships. We applied these criteria to the relationships in the class "real person" of STNet and the result shows that 1,135 out of 1,743 uncertain relationships such as RT, RT_X or RT_Y are specified and clarified. This rate of optimization with ca. 65% represents the usefulness of the criteria applicable to the cases of database construction and retrieval.

• Journal of Mushroom
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• v.4 no.4
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• pp.144-213
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• 2006

The mushroom production reached to 1000 billion won in monetary value in Korea. We, however, do not have systematic terminology dictionary published yet. Recently new varieties of medicinal mushrooms in addition to culinary mushrooms are being introduced steadily through out the world. This makes the necessity of coordinated and consistent arrangement of terms involved in culture, cultivation and physiological aspects of mushrooms. Various components in relation to the medicinal and physiological functionality also poses ambiguity in terminology along with the terms used in breeding and genetic researches. Moreover, some of the scientific terms are being used erroneously. In order to help mushroom cultivators, students, and mushroom business personnel in understanding the terms on mushroom science and technology we intended to collect and organize all the terms related to mushroom morphology and cultivation, poison and medicinal functionality, processing and utilization, and so on. Thirteen professionals from each field participated in this project. The fields included here are : 1) Genetics and breeding of mushrooms, 2) Cultivation and physiology of mushrooms, 3) Taxonomy and ecology of mushrooms, 4) Processing and functional components, 5) Blight and insects of mushrooms.

• Journal of Information Management
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• v.40 no.4
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• pp.1-22
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• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.