• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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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.

• 재활치료과학
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• 제12권4호
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• pp.39-51
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• 2023

목적 : 본 연구는 국내 학술지를 대상으로 아동의 작업과 관련된 연구주제어의 사회연결망 분석을 통해 아동의 작업과 관련된 연구들의 지적 구조를 규명하고자 한다. 연구방법 : 2003년 8월부터 2023년 8월까지 한국학술지인용색인(Korean Citation Index)에 "아동 and 작업" 키워드를 가진 270편의 연구에서 3,364개의 키워드를 추출하여 분석하였다. 분석도구는 넷마이너(NetMiner) 프로그램을 활용하였다. 결과 : 연구 시기별 아동의 작업 관련 연구주제어의 변화는 없었으며 다만 과거 10년에는 97편의 연구가 있었고 최근 10년에는 173편의 연구가 게재되어 양적 변화가 있었다. 아동의 작업 관련 주제어에서 가장 높은 연결 중심성(degree centrality)을 가진 단어는 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), Program (0.023) 순이었다. 단어동시 발생 네트워크(Word network)에서 가장 가중치가 높은 단어는 Evaluation-Tool (30), School-Student (15), Activity-Participation (15)이었고, topic modeling에서 각 주제들의 첫 번째 키워드는 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), Training (0.511)으로 나타났다. 결론 : 본 연구는 국내 아동의 작업 관련 연구 분야의 경향을 설명했다. 따라서 국외와 국내 연구 흐름을 비교하는 후속 연구가 뒤따라야 할 것이며, 이러한 노력은 국내 연구와 국외 연구의 격차를 해명함으로써 국내 아동의 작업관련 연구 분야에 대한 귀중한 통찰력을 제공할 것이다.

• International Journal of Contents
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• 제13권3호
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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.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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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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• 제22권1호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 95 KFIS Workshop Realization of Human Friendly System Based on Soft Computiong Techniques
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• pp.55-123
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• 1995

• 전자공학회논문지C
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• 제34C권2호
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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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• 제21권3호
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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.

• 인터넷정보학회논문지
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• 제25권4호
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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.

• 인터넷정보학회논문지
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• 제17권5호
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• pp.59-65
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• 2016

최근 세계적으로 에너지 부족 문제를 해결하기 위해 에너지저장시스템에 관한 연구가 활발히 이루어지고 있다. 에너지저장시스템은 에너지 네트워크상의 모든 에너지 인프라에 대한 모니터링 및 제어를 통해 ESS(Energy Storage System) 에너지 사용을 극대화할 수 있다. 하지만 에너지저장시스템의 주요 부품이나 장치들 간의 호환 문제는 ESS 제품 개발에 걸림돌로 작용하고 있다. 이를 해결하기 위해 ESS 부품 및 장치들의 특성을 확장 할 수 있는 프로파일과 이를 검증할 수 있는 소프트웨어 기술이 요구되어지고 있다. 본 논문에서는 에너지저장장치용 확장성 프로파일 검증 소프트웨어의 구조에 따른 복잡도 분석에 관한 연구를 수행한다. 프로파일 검증 소프트웨어 분석을 위해 기존의 XML(eXtensible Markup Language) 기반의 프로파일과 C언어 구조체 기반의 프로파일을 사용한다. XML 기반의 프로파일을 여러번 파싱하는 복잡한 검증 구조와 파싱 절차를 감소하고 단순 반복을 이용한 C언어 구조체 기반의 검증 소프트웨어의 복잡도를 분석하고 비교한다. 시간 복잡도, 공간 복잡도 및 순환 복잡도 알고리즘을 이용하여 XML 기반의 프로파일과 C언어 구조체 기반의 프로파일 검증 소프트웨어의 복잡도를 비교 및 분석하여 연구 결과를 제시한다.