• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.251-256
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• 2021

This study analyzed the most frequently used navigation cases in a desktop environment. As a result of the research, GNB induces users' search as the top element of the search structure and can place color, text, icon, and image elements. LNB could be classified in the form of a dropdown, flyout, dropline and mega menu. In this study, the navigation structure of Interpark and Interpark among open markets used by users was analyzed. G-Market's GNB has a two-tier structure with color, text, image, and icon elements, and Interpark has a three-tiered horizontal label. Interpark's GNB drew attention by placing a badge on the seasonal label, which is a temporary content section, unlike G-market. It can be seen that the LNBs of both shopping malls have flyout menus that protrude when you mouse over the category menu arranged in a vertical text form under the logo placed on the left. The flyout menu has a complex structure consisting of the layout of the mega menu. This study is meaningful in revealing user experience elements by analyzing the GNB and LNB of shopping malls these days where internet shopping is increasing.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.470-471
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• 2018

본 논문에서는 소형 큐브위성의 전력시스템 구성품의 용량 및 위성의 운용로직을 설계할 수 있는 소프트웨어 테스트베드 설계 방법을 제시한다. 기존 초소형 인공위성 시스템 설계를 위한 소프트웨어가 개발되어 상용품으로 판매되고 있으나, 주로 자세제어 시스템의 제어기 설계를 위해 소프트웨어가 사용되고있고, 텍스트기반 복잡한 구조로 되어있어 본 논문의 목적인 전력계 구성품 용량 및 운용로직을 설계하는데 이를 활용하기 어려운 측면이 있었다. 따라서 본 논문에서는 전력시스템의 구성품들을 전력 및 에너지 방정식으로 모델링하여 Matlab/Simulink에서 이를 구현함으로써 가독성을 높여 시스템 설계 및 분석 시간을 줄일 수 있는 소프트웨어 테스트베드 설계방법을 제시한다. 제안된 소프트웨어 테스트베드를 이용한 3리터 사이즈의 소형 큐브위성 시스템의 구성품 용량 및 운용로직 설계 결과를 본 논문에서 제시한다.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.667-674
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• 2004

Extraction of texts from images is a fundamental and important problem to understand the images. This paper suggests a text region verification method by statistical means of stroke features of the characters. The method extracts 36 dimensional features from $16\times16$sized text and non-text images using wavelet transform - these 36 dimensional features express stroke and direction of characters - and select 12 sub-features out of 36 dimensional features which yield adequate separation between classes. After selecting the features, SVM trains the selected features. For the verification of the text region, each $16\times16$image block is scanned and classified as text or non-text. Then, the text region is finally decided as text region or non-text region. The proposed method is able to verify text regions which can hardly be distin guished.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.513-524
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• 2020

Recently, YouTube's growth started drawing attention. YouTube is not only a content-consumption channel but also provides a space for consumers to express their intention. Consumers share their opinions on YouTube through comments. The study focuses on the text of global entrepreneurs' speeches and the comments in response to those speeches on YouTube. A content analysis was conducted for each speech and comment using the text mining software Leximancer. We analyzed the theme of each entrepreneurial speech and derived topics related to the propensity and characteristics of individual entrepreneurs. In the comments, we found the theme of money, work and need to be common regardless of the content of each speech. Talking into account the different lengths of text, we additionally performed a Prominence Index analysis. We derived time, future, better, best, change, life, business, and need as common keywords for speech contents and viewer comments. Users who watched an entrepreneur's speech on YouTube responded equally to the topics of life, time, future, customer needs, and positive change.

• Journal of the Korean Society for information Management
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• v.37 no.3
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• pp.253-274
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• 2020

In this study, text mining and main path analysis (MPA) were applied to understand the origins and development paths of research areas that make up the mainstream of Korean studies. To this end, a quantitative analysis was attempted based on digital texts rather than the traditional humanities research methodology, and the main paths of Korean studies were extracted by collecting documents related to Korean studies including citation information using a citation database, and establishing a direct citation network. As a result of the main path analysis, two main path clusters (Korean ancient agricultural culture (history, culture, archeology) and Korean acquisition of English (linguistics)) were found in the key-route search for the Humanities field of Korean studies. In the field of Korean Studies Humanities and Social Sciences, four main path clusters were discovered: (1) Korea regional/spatial development, (2) Korean economic development (Economic aid/Soft power), (3) Korean industry (Political economics), and (4) population of Korea (Sex selection) & North Korean economy (Poverty, South-South cooperation).

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.282-290
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• 2018

This study tried to suggest the development of a writing education model for Christian Universities based on both Hobbs' media education model and Vanhoozer's media text analysis model. This model consists of 6 steps- Christian worldview establishment, access, analysis and evaluation, creation, reflection and social action. This was developed in order to be applied for the class "reading and writing" of liberal arts. Also, this is an appropriate model for media text writing education aiming at an alternative creation activity through a critical comprehension of the complex texts consisting of sounds, images, letters and so on. Furthermore, this is designed to train the capable persons having intelligence, character, and spirituality balanced, whom the education of Chrisitian universities aims at. Finally, this model pursues the student-friendly and amalgamative text writing appropriate for a new era and has an advantage to raise the power of various forms of letter writing which all the universities should stress as well.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.65-73
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• 2013

As the advent of the digital age, documents are often scanned to be archived or to be transmitted over the network. The largest proportion of documents is texts and the next is seal images indicating the author of the documents. While a lot of research has been conducted to recognize texts in scanned documents and commercialized text recognizing products are developed as highlighted the importance of the scanned document, information about seal images is discarded. In this paper, we study how to extract the seal image area from the color or black and white document containing the seal image and how to save the seal image. We propose a preprocessing step to remove other components except for the candidate outlines of the seal imprint from scanned documents and a method to select the final region of interest from these candidates by using the feature of seal images. Also in case of a seal imprint overlapped with texts, the most similar image among those stored in the database is selected through the template matching process. We verify the implemented system for a various type of documents produced in schools and analyze the results.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.103-110
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• 2015

Sentiment lexicon is an essential element for expressing sentiment on a text or recognizing sentiment from a text. We propose a graph-based semi-supervised learning method to construct a sentiment dictionary as sentiment lexicon set. In particular, we focus on the construction of domain-specific sentiment dictionary. The proposed method makes up a graph according to lexicons and proximity among lexicons, and sentiments of some lexicons which already know their sentiment values are propagated throughout all of the lexicons on the graph. There are two typical types of the sentiment lexicon, sentiment words and sentiment phrase, and we construct a sentiment dictionary by creating each graph of them and infer sentiment of all sentiment lexicons. In order to verify our proposed method, we constructed a sentiment dictionary specific to the movie domain, and conducted sentiment classification experiments with it. As a result, it have been shown that the classification performance using the sentiment dictionary is better than the other using typical general-purpose sentiment dictionary.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.227-248
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• 2017

This paper introduces an integrated model for systematically constructing a linguistic resource database that can be used by machine learning-based biomedical information extraction systems. The proposed method suggests an orderly process of collecting and constructing dictionaries and training sets for both named-entity recognition and relation extraction. Multiple heterogeneous structures for the resources which are collected from diverse sources are analyzed to derive essential items and fields for constructing the integrated database. All the collected resources are converted and refined to build an integrated linguistic resource storage. In this paper, we constructed entity dictionaries of gene, protein, disease and drug, which are considered core linguistic elements or core named entities in the biomedical domains and conducted verification tests to measure their acceptability.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.132-139
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• 2013

This research considered the aesthetic factors of the Korean style superhero film through the analysis of text of . Basically, the various elements including the structure of the story, characters, mise en scene, and etc. are included in the aesthetic factors. Therefore, in this research, the organization of other aesthetic elements and characteristics including the characters and mise en scene, and etc. were analyze based upon the first analysis about the structure of . And the theoretical backgrounds for the research were 'The Poetics' of Aristotle. The reason why this movie selects the movie as the research text specially was that had the plot and genre style compared with the existing Hollywood superhero film. Consequently, the research could find the communities and differences for the aesthetic features between Hollywood superhero film and .