• The Journal of Information Systems
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• v.25 no.4
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• pp.121-139
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• 2016

Purpose In this study, we propose the special purposed R package named ""new_Noun()" to process nonstandard texts appeared in various social networks. As the Big data is getting interested, R - analysis tool and open source software is also getting more attention in many fields. Design/methodology/approach With more than 9,000 R packages, R provides a user-friendly functions of a variety of data mining, social network analysis and simulation functions such as statistical analysis, classification, prediction, clustering and association analysis. Especially, "KoNLP" - natural language processing package for Korean language - has reduced the time and effort of many researchers. However, as the social data increases, the informal expressions of Hangeul (Korean character) such as emoticons, informal terms and symbols make the difficulties increase in natural language processing. Findings In this study, to solve the these difficulties, special algorithms that upgrade existing open source natural language processing package have been researched. By utilizing the "KoNLP" package and analyzing the main functions in noun extracting command, we developed a new integrated noun processing package "new_Noun()" function to extract nouns which improves more than 29.1% compared with existing package.

• Therapeutic Science for Rehabilitation
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• v.12 no.4
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• pp.39-51
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• 2023

Objective : This study seeks to unveil the intellectual framework of research surrounding children's occupations by utilizing social network analysis of keywords from studies focused on childhood. Methods : From August 2003 to August 2023, we analyzed 3,364 keywords extracted from 270 research articles in the Korean Citation Index with the keyword "Child and Occupation" using the NetMiner program. Results : Research on children's work has increased quantitatively over the past decade. Keywords exhibiting a high degree of centrality in the realm of child occupation research included Task (0.055), Group therapy (0.040), Working memory (0.037), Intervention (0.033), Performance (0.030), Language (0.026), Ability (0.026), Skill (0.024), and Program (0.023). Notably, the weighted terms in the Word Network included Evaluation-Tool (30), School-Student (15), and Activity-Participation (15). The primary keywords from each topic in topic modeling were Activity (0.295), Disability (0.604), Education (0.356), Skill (0.478), School (0.317), Function (0.462), Disorder (0.324), Language (0.310), Comprehension (0.412), and Training (0.511). Conclusion : This study describes the trends in the domestic field of pediatric occupational research. These efforts provided valuable insights into pediatric occupational therapy in South Korea.

• International Journal of Contents
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• v.13 no.3
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• pp.38-42
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• 2017

Documents of the last few decades typically include more than one kind of language, so linguistic classification of each word is essential, especially in terms of English and Korean in handwritten documents. Traditional methods mostly use conventional features of structural or stroke features, but sometimes they fail to identify many characteristics of words because of complexity introduced by handwriting. Therefore, traditional methods lead to a considerably more-complicated task and naturally lead to possibly poor results. In this study, convolutional neural network (CNN) is used for classification of English and Korean handwritten words in text documents. Experimental results reveal that the proposed method works effectively compared to previous methods.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.389-393
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• 2018

딥러닝의 발달로 기계번역, 대화 시스템 등의 자연언어처리 분야가 크게 발전하였다. 딥러닝 모델의 성능을 향상시키기 위해서는 많은 데이터가 필요하다. 그러나 많은 데이터를 수집하기 위해서는 많은 시간과 노력이 소요된다. 본 연구에서는 이미지 생성 모델로 좋은 성능을 보이고 있는 생성적 적대 네트워크(Generative adverasarial network)를 문장 생성에 적용해본다. 본 연구에서는 긍/부정 조건에 따른 문장을 자동 생성하기 위해 SeqGAN 모델을 수정하여 사용한다. 그리고 분류기를 포함한 SeqGAN이 긍/부정 감성인식 학습데이터를 자동 생성할 수 있는지 실험한다. 실험을 수행한 결과, 분류기를 포함한 SeqGAN 모델이 생성한 문장과 학습데이터를 혼용하여 학습할 경우 실제 학습데이터만 학습 시킨 경우보다 좋은 정확도를 보였다.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.93-96
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• 2022

Natural language processing (NLP) is utilized to understand a natural text. Text analysis systems use natural language algorithms to find the meaning of large amounts of text. Text classification represents a basic task of NLP with a wide range of applications such as topic labeling, sentiment analysis, spam detection, and intent detection. The algorithm can transform user's unstructured thoughts into more structured data. In this work, a text classifier has been developed that uses academic admission and registration texts as input, analyzes its content, and then automatically assigns relevant tags such as admission, graduate school, and registration. In this work, the well-known algorithms support vector machine SVM and K-nearest neighbor (kNN) algorithms are used to develop the above-mentioned classifier. The obtained results showed that the SVM classifier outperformed the kNN classifier with an overall accuracy of 98.9%. in addition, the mean absolute error of SVM was 0.0064 while it was 0.0098 for kNN classifier. Based on the obtained results, the SVM is used to implement the academic text classification in this work.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10a
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• pp.55-123
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• 1995

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.2
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• pp.61-70
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• 1997

Human-hand gestures have been used a means of communication among people for a long time, being interpreted as streams of tokens for a language. The signed language is a method of communication for hearing impaired person. Articulated gestures and postures of hands and fingers are commonly used for the signed language. This paper presents a system which recognizes the korean sign language (KSL) and translates the recognition results into a normal korean text and sound. A pair of data-gloves are used a sthe sensing device for detecting motions of hands and fingers. In this paper, we propose a dynamic gesture recognition mehtod by employing a fuzzy feature analysis method for efficient classification of hand motions, and applying a fuzzy min-max neural network to on-line pattern recognition.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.76-82
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• 2021

An anthological analysis of known literature and historical sources is carried out in the work. It was found that the development of foreign language training of future professionals was influenced by a number of factors: socio-economic (focus on the needs of the labor market, integration into the international space, scientific and technological progress); educational (updating legal documents in the field of education, standardization of educational content, development of methods of professional development of a specialist). The historical period is analyzed and the following stages are determined: ideological (realization of ideological imperative in language and professional training of future specialists; educational-methodical (preparation according to unified curricula, reading and translation as a leading type of speech activity); integration (integration of foreign language teaching and multicultural education)), methodological (use of traditional verbal methods, standardized textbooks). Thus, the research conducted in the article indicates the periods (stages) of formation, functioning and development of foreign language education.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.73-86
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• 2024

With the acceleration of regional economic integration, the agricultural trade network within the RCEP region presents new opportunities and challenges for member countries. This study focuses on agricultural trade among RCEP members from 2011 to 2020, utilizing social network analysis to explore the structural characteristics and evolutionary trends of the trade network. Additionally, an extended gravity model is employed to empirically analyze the key factors influencing South Korea's agricultural trade with other member countries. The findings reveal that: (1) Agricultural trade relationships within the RCEP region are stable and mature, with high interconnectivity in the trade network, indicating a trend towards balanced development. (2) The positions of member countries within the agricultural trade network are characterized by both high density and heterogeneity. (3) South Korea's agricultural trade with RCEP member countries is positively influenced by the economic size, population size, and governance level of its trading partners, while South Korea's own indicators show no significant effect. The trade distance between South Korea and member countries also has a positive impact on agricultural trade. By combining social network analysis with an extended gravity model, this study provides a multi-faceted quantitative analysis of the RCEP agricultural trade network, offering new insights into regional agricultural trade. It also provides empirical evidence for agricultural trade cooperation between South Korea and other RCEP countries.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.59-65
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• 2016

Recently, a study has been progressed about the energy storage system for resolving energy shortage problems in the world. The energy storage system can maximize energy storage system's energy usage by monitoring and controlling about all energy infrastructures on energy network. However, compatibility problems among main components or devices of the energy storage system are obstacles to development of energy storage system products. An extensible profile and extensible profile verification software being able to verify the extensible profile have been required in order to resolve compatibility problems. In this paper, the study on complexity analysis for the extensible profile verification software for the energy storage system is performed. A XML based profile and C language structure based profile are used for analysis of the profile verification software. The complexity of complex verification structure that parses the XML based profile several times and simple verification structure that parses the C language structure based profile are analyzed and compared. Time complexity, space complexity, and cyclomatic complexity are used for complexity analysis. By using these complexity analysis, the study result that compares and analyzes the complexity of XML based and C language structure based profile verification software is presented.