• Journal of Digital Convergence
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• v.19 no.1
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• pp.307-314
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• 2021

This study aimed to apply the principle of the semantic network to a long novel in an attempt to understand the structure of the entire document and the manifested relationships between words and words. The costume expressions in Murakami's novel Norwegian Wood were analyzed based on the characters' symbols, relationships, and personality characteristics. The study identified the symbols of the characters in the novel and the relationship properties between the characters through the Clauset-Newman-Moore clustering algorithm. The descriptions and symbols of the relationships between the characters were identified within the worldview that the author had intended. Further, it was confirmed that the expression of each costume according to the character's personality was also connected to the clue that explained said character. This fusion study is academically significant in that it presents a new methodology for analyzing literary works

• Journal of the Korean Society of Costume
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• v.62 no.5
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• pp.1-15
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• 2012

In a fast changing postmodern society, contemporary fashion is becoming more complicated and ambiguous along with other genres of art than ever before. This phenomenon reigning as a sociocultural paradigm can be defined as 'indeterminacy' and it means 'undecidability'. The purpose of this study is to clarify and analyze the indeterminate characteristics of contemporary fashion reviewing the theoretical background and the architectural formativeness as a comparative research. The core idea of deconstructivism dismantles a causal relationship between function and form in fashion and the conventional notion about clothes. Complexity theory, which is the study of chaotic dynamical systems, suggests the creative idea and concept of infinite possibilities on a formative method. Meanwhile, catastrophe theory of discontinuous change can be used as interpretative strategies for the process of deconstruction and reconstruction. As a result of this study, the indeterminacy of fashion can be analyzed into five semantic categories: irregularity, immateriality, randomness, complexity and changeability. The intrinsic value of the indeterminacy in contemporary fashion is the interaction with a sociocultural ideology and a technological environment as well as an expansion of formative expression. To conclude, it can be said that the indeterminacy in fashion is a new interpretation of the relationship among body and space, clothes and society.

• Korean Institute of Interior Design Journal
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• v.21 no.6
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• pp.147-157
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• 2012

This paper aims to examine the fundamental relationship of what principles cause the aesthetic shapes in Korean sarangbang furniture of the $19^{th}$ century. Focusing on the Greimas' isotopic and semantic structure analysis, this research analyzed the traditional Korean men's furniture in four steps; signifier analysis, isotopic analysis, semantic structure analysis, and comprehensive interpretation. The results show that the expressive qualities of sarangbang furniture included visual symmetric aesthetics, and the hues of natural materials with dark tones. The manufacturing process emphasized the characteristics of natural materials; while diversity was respected in decorations, function as restrained form was also important with a concise image. Through these characteristics, sarangbang furniture revealed a balance, a harmony of contrastive elements, and a restrained aesthetics. Within these qualities, it was seen that aesthetic principles, such as "severance and communication," "artifice and nature," "restraint and manifestation," "toughness and softness," "filling and emptying" and "decoration and utility" were in a mutually supplementary relationship. At the basis of this aesthetic thought appears to be Confucianism, which had been the model for seonbi politics and scholarship.

• Culinary science and hospitality research
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• v.24 no.3
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• pp.167-176
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• 2018

In this study, Big Data was used to collect the information related to 'Cooking Academy' keywords. After collecting all the data, we calculated the frequency through the text mining and selected the main words for future data analysis. Data collection was conducted from Google Web and News during the period from January 1, 2013 to December 31, 2017. The selected 64 words were analyzed by using UCINET 6.0 program, and the analysis results were visualized with NetDraw in order to present the relationship of main words. As a result, it was found that the most important goal for the students from cooking school is to work as a cook, likewise to have practical classes. In addition, we obtained the result that SNS marketing system that the social sites, such as Facebook, Twitter, and Instagram are actively utilized as a marketing strategy of the institute. Therefore, the results can be helpful in searching for the method of utilizing big data and can bring brand-new ideas for the follow-up studies. In practical terms, it will be remarkable material about the future marketing directions and various programs that are improved by the detailed curriculums through semantic network of cooking school by using big data.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.953-957
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• 2009

This paper proposes a keyword-based query translation system for the semantic web. With the relationship between keywords and ontology structure information, the system converts keyword based queries into queries written by formal query language which is appropriate for the semantic web. As a result, casual web users could not only express queries easily but also obtain the better result.

• Journal of Korean Library and Information Science Society
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• v.32 no.4
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• pp.77-98
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• 2001

As the role of a library has changed to the integrated management system of knowledge, the library needs new information retrieval tools. The purpose of this study is to propose a method and principle of the Korean-English semantic thesaurus construction for a knowledge management system. The method and principle is as follows; 1) in collecting terminology, I included not only internal documents but external documents on the web as a source for the descriptors extraction. 2) conceptual descriptors are more needed than semantic ones. I also proposed the necessity of the authority files for complement. 3) I proposed the appropriate scale of the descriptors to be 15,000 in a thesaurus. And 4) I proposed a hybrid method that used both a manual and an automatic process in establishing the relationship.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.129-142
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• 2018

Recently, the number of patent applications have been increasing rapidly every year as the importance of protecting intellectual property rights becomes more important. Patents must be inventive and have novelty. Especially, the novelty implies that the corresponding invention is not the same as the previous invention. To confirm the novelty, prior art search must be conducted before and after the application. The target of prior art search should include not only Korean patents but also foreign patents. Search of foreign patents should be supported by multilingual search techniques. However, a dictionary-based naive approach shows a limitation because some technical concepts are represented in different terms according to each nation. For example, a Korean term and a Japanese term may not be synonym even though they represent the same technical concept. In this paper, we propose a new method to map semantic similarity between technical terms in Korean patents and Japanese patents. To investigate different representations in each nation for the same technical concept, we identified and analyzed pairs of patents those are mutually connected with priority claim relationship. By performing an experiment with real-world data, we showed that our approach can reveal semantically similar technical terms in other language successfully.

• Journal of Contemporary Eastern Asia
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• v.11 no.1
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• pp.1-20
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• 2012

This study analyzes messages from Korean TV debates on the conflict over U.S. beef imports and the process of negotiations over the imports in 2008. The authors have conducted a content analysis and a semantic network analysis by using KrKwic and CONCOR. The data was drawn from nine TV debates aired by three major TV networks in Korea (MBC, KBS, and SBS) from 27 April 27 2008 to 6 July 2008. The results indicate substantial differences in the semantic structure between arguments by the government and those by civic groups. We also investigated the relationship between the terms frequently used by both sides (i.e., the government and civic groups), and the terms used exclusively by one side. There was a gradual increase in the number of terms frequently used by both sides over time, from the formation of the conflict to its escalation to its resolution. The results indicate the possibility of general agreement in conflict situations.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1879-1890
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• 2011

Previous studies of syllable frequency effects have proposed that inhibitory effects due to high first syllable frequency were the products of competitions between activated lexical candidates within a lexical level. However, these studies have primarily used lexical decision tasks to examine the nature of syllable frequency effects. This study investigates whether a syllable frequency effect can arise in semantic categorization tasks and whether phonologically or orthographically defined syllables interact with semantically related variables such as morphological family size. If the syllable frequency effect was created by activations and competitions on a lexical level, it is highly possible that the effect was related to semantic categorization tasks. To test this hypothesis, we conducted two experiments. In Experiment 1, morphological family size and phonological syllable frequency were factorially manipulated. In Experiment 2, morphological family size and orthographic syllable frequency were factorially manipulated. The results demonstrate that morphemes have no relationship with phonological syllables but do with orthographic syllables. This suggests that phonological syllables and orthographic syllables have different roles in the syllable frequency effect on visual word recognition process.