• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.63-69
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• 2015

There are various researches which proposed an automatic instance generation from freetext on the web. Existing researches that focused on English, adopts pattern representation which is generated by simple rules and regular expression. These simple patterns achieves high performance, but it is not suitable in Korean due to differences of characteristics between Korean and English. Thus, this paper proposes a novel method for generating patterns and instances which focuses on Korean. A proposed method generates high quality patterns by taking advantages of dependency relations in a target sentences. In addition, a proposed method overcome restrictions from high degree of freedom of word order in Korean by utilizing postposition and it identifies a subject and an object more reliably. In experiment results, a proposed method shows higher precision than baseline and it is implies that proposed approache is suitable for self-knowledge learning system.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.499-517
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• 2008

In this paper, we propose an effective emotion feature extraction method for Korean and evaluate their availability in sentiment classification. Korean emotion features are expanded from several representative emotion words and they play an important role in building in an effective sentiment classification system. Firstly, synonym information of English word thesaurus is used to extract effective emotion features and then the extracted English emotion features are translated into Korean. To evaluate the extracted Korean emotion features, we represent each document using the extracted features and classify it using SVM(Support Vector Machine). In experimental results, the sentiment classification system using the extracted Korean emotion features obtained more improved performance(14.1%) than the system using content-words based features which have generally used in common text classification systems.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.174-183
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• 2017

In this paper, we propose a novel feature for recognizing handwritten Odia numerals. By using polygonal approximation, each numeral is segmented into segments of equal pixel counts where the centroid of the character is kept as the origin. Three primitive contour features namely, distance (l), angle (${\theta}$), and arc-tochord ratio (r), are extracted from these segments. These features are used in a neural classifier so that the numerals are recognized. Other existing features are also considered for being recognized in the neural classifier, in order to perform a comparative analysis. We carried out a simulation on a large data set and conducted a comparative analysis with other features with respect to recognition accuracy and time requirements. Furthermore, we also applied the feature to the numeral recognition of two other languages-Bangla and English. In general, we observed that our proposed contour features outperform other schemes.

• Journal of Practical Engineering Education
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• v.7 no.2
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• pp.135-146
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• 2015

This study aimed for testing the effects of the empowerment in the circumstances of remote management that managers and employees were in separate countries. For this purpose, researchers collected survey data from 79 local teachers in multinational enterprises on English education and performed Structural Equation Modeling. The hypotheses below are revealed as significant. Firstly, empowerment had a positive effect on job satisfaction, but had a negative effect on job stress. Secondly, empowerment had a positive effect on organizational commitment. Thirdly, job satisfaction had a positive effect on organizational commitment. Fourthly, job stress had a negative effect on organizational commitment and job satisfaction mediated the relationship between empowerment and organizational commitment. Finally, job stress mediated the relationship between empowerment and organizational commitment. And the results of this study suggest that the employees' job satisfaction and organizational commitment can be enhanced using empowerment in the remote management system.

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.315-322
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• 2000

본 논문에서는 공군 정보 번역을 위한 영한 기계번역 시스템 ALKOL에 대해서 소개한다. ALKOL은 어휘화된 규칙에 기반한 번역 시스템으로, 어휘화된 규칙은 어휘-분석-변환-생성의 네 단계의 정보가 연결된 형태로 사전에 저장된다. 이와 같은 사전 구조에 의해 번역 과정의 효율성을 높일 수 있고, 어휘화된 규칙에 의해 정확하고 자연스러운 번역 결과를 얻을수 있다. ALKOL의 번역 과정은 형태소 분석, 품사 태깅, 분석 전처리, 구문 분석, 변환, 생성의 단계로 이루어진다. 각 단계에서는 전/후처리를 보강하여 실제 번역 환경에서 나타나는 문제들을 해결하고, 하나 이상의 번역 결과를 출력하여 사용자가 원하는 결과를 선택할 수 있게 한다.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.113-124
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• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.757-763
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• 2019

Youtube has become so popular that it is called the age of YouTube. As the number of users and contents increase, the choice of information increases. However, it is difficult to select information that meets the needs of users. YouTube provides recommendations based on their watch list. Therefore, in this study, we want to analyze the channel of user's subject in various angles and provide the proposed scheme based on the crawled channels, measurement of the perception of channels and channel videos through quantitative data and hidden qualitative data analysis. Based on the above two data analysis, it is possible to know the recognition of the channel and the recognition of the channel video, thereby providing a ranking of the channels that deal with the topic. Finally, as a case study, we recommend English learning channels to users based on numerical data statistics and emotional analysis results to maximize flipped learning effect regardless of time and space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.279-288
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• 2018

In this paper, we present the results of educational innovation case study using U-Learning Box and Ubiquitous-based Test(UBT) system for 6 sample primary schools in Nepal. As Nepal is considered to be a developing country with electricity problem to the school, the U-Learning Box, consisting of a small and easy-to-use tablet PC for teacher and a small smart beam with its own battery was evaluated as the optimum solution to support continuous basic English and hygiene education for these schools. And UBT technology using tablet PC was used to evaluate and analyze basic English learning ability of the students, which helped us realized that it is necessary to improve the educational environment and develop suitable educational contents. We hope that the global educational innovation using U-Learning Box and UBT technology will become a successful model for global equality of educational opportunity project for developing countries including Nepal.

• IE interfaces
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• v.20 no.2
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• pp.133-141
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• 2007

As the sales of the Sports Toto, the Korean lottery on sports games, have increased significantly in recent five years, interest in predicting the various results of sports matches has also been raised. Dixon and Coles (1997) proposed a bivariate Poisson model to predict the results of English soccer league matches. In this paper, we pay attention to the physical condition of players that may affect soccer match results and revise Dixon and Coles' model to consider probable fatigue due to the players' short rest followed by their frequent matches. We observed the fatigue effect in the match results, and found positive betting returns available when using our prediction model. Furthermore, the validity of probability-based odds in European and Korean betting markets is analyzed.