• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.468-471
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• 2004

In this paper, a method for classifying fingerprint ridge lines using runlength codes is proposed. To detect feature points(minutiae) in automatic fingerprint identification system(AFIS), classification of fingerprint ridge lines are essential process. The fingerprint ridge lines are classified by run-length coding, and also the end and bifurcation regions in ridge lines are separated. To evaluate the performance of the proposed method, detected feature regions including minutiae points and classified fingerprint ridge lines are shown.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.53-54
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• 2018

본 논문에서는 스펙트로그램을 이용하여 딥 러닝 기반으로 오디오 장르와 품질의 다중 정보를 동시에 분류하는 기술을 제안한다. 기존 딥 러닝 기반의 오디오 정보 인식 기술은 각각의 정보 인식을 목표로 독립 네트워크를 설계하고, 여러 정보를 동시에 인식하기 위하여 각각에 특화된 여러 네트워크를 사용한다. 이러한 문제점을 보완하기 위해 본 논문에서는 디지털 오디오의 대표 특성인 스펙트로그램을 기반으로 범용성이 있는 특성을 추출하고, 단일 네트워크로 학습시켜 장르 및 품질을 동시에 분류하는 다중 분류 기술을 제안한다. 제안하는 방법으로 단일 분류 성능과 유사한 다중 분류 성능을 얻을 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.109-111
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• 2011

대부분의 빈발 부분그래프를 이용한 그래프 분류 알고리즘들은 빈발 부분그래프를 마이닝하여 개별적인 빈발 부분그래프의 포함 여부를 특징 벡터로 구성하는 단계와 기계학습 알고리즘들을 훈련시켜 분류 모델을 수립하는 단계로 구성된다. 이와 같은 그래프 분류 알고리즘들은 부분그래프의 개별적인 존재 여부만을 이용하여 특징을 구성하기 때문에 변별력이 떨어지는 문제점이 있다. 본 논문에서는 빈발 부분그래프들이 동시 발생하는 특징 벡터의 변별력을 반영할 수 있는 특징선택 기법을 적용한 모델 기반 탐색트리 기법을 제안한다. 동시 발생 부분그래프를 특징으로 사용하여 변별력을 향상시킬 수 있으며, 모델기반 탐색 트리를 사용하여 제안하는 기법이 기존의 방법보다 더 높은 그래프 분류 성능을 보이는 것을 입증하였다.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.870-878
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• 2013

In this paper, we propose a novel fingerprint classification method to enhance the accuracy and efficiency of the fingerprint identification system, one of biometrics systems. According to the previous researches, fingerprints can be categorized into the several patterns based on their pattern of ridges and valleys. After construction of fingerprint database based on their patters, fingerprint classification approach can help to accelerate the fingerprint recognition. The reason is that classification methods reduce the size of the search space to the fingerprints of the same category before matching. First, we suggest a method to extract region of interest (ROI) which have real information about fingerprint from the image. And then we propose a feature extraction method which combines gray level co-occurrence matrix (GLCM) and wavelet features. Finally, we compare the performance of our proposed method with the existing method which use only GLCM as the feature of fingerprint by using the multi-layer perceptron and support vector machine.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.33-57
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• 2017

This study aims to introduce an emerging prescriptive analytics method and suggest its efficient application to a category-based service system. Prescriptive analytics method provides the whole process of analysis and available alternatives as well as the results of analysis. To simulate the process of optimization, large scale journal articles have been collected and categorized by classification scheme. In the process of applying the concept of prescriptive analytics to a real system, we have fused a dynamic automatic-categorization method for large scale documents and intellectual structure analysis method for scholarly subject fields. The test result shows that some optimized scenarios can be generated efficiently and utilized effectively for reorganizing the classification-based service system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.262-267
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• 2008

본 논문에서는 문서 내에서 동시에 출현하는 단어 쌍을 자질 추출 단위로 하는 문서 범주화 시스템에 대하여 기술한다. 자질 추출 단위를 단어 쌍으로 정의한 것은 문서에서 빈번하게 동시에 출현하는 단어들은 서로 연관관계가 높으며, 단어 하나보다는 연관관계가 높은 단어들의 쌍이 특정 범주의 문서에서만 나타날 확률이 높아지므로 문서 분류 능력을 높이는데 좋은 요인으로 작용할 수 있을 것이라는 가정 때문이다. 그리고 문서 요약 분야에서 제안된 Log-likelihood Ratio를 기반으로 하는 Topic Signature Term Extraction 방법을 사용하여 자질 추출을 하고, Naive Bayes 분류기를 이용하여 문서를 분류한다. 본 연구는 Reuters-21578 문서 집합을 이용한 성능평가에서 좋은 결과를 보였으며, 이는 앞으로의 연구에도 기여할 수 있을 것이라 기대한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.519-520
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• 2024

KOICD(질병분류 정보센터), 보건의료정보표준, 질병분류기호 모두 국내에서 권위 있는 질병분류 정보 검색 가능 홈페이지를 가지고 있다. 그러나 국내에서 가장 많이 이용되는 KCD 와, 국제적으로 사용되는 SNOMED CT 의 검색결과가 동시에 나오는 사이트는 아직 존재하지 않는다. 이에 의료진과 환자, 보험사의 편의를 모두 고려하여 KCD 와 SNOMED CT 가 동시에 출력되는 검색사이트를 제작하였다.

• Journal of Korea Technology Innovation Society
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• v.10 no.3
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• pp.531-554
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• 2007

This paper suggests a new model connecting various knowledge activities through classification systems such as classifications of research, technology, industry, major and job. Although research activities are linked to technology and industry areas or to education and job areas, there is no effort to link these kinds of activities. There are a few studies to link research and technology or research and education respectively. But, there have been no studies to connect technology-industry linkage and education-job linkage. This paper suggests that research area can be a basis of link between technology-industry linkage and education-job linkage. The methods building the links are not simple, but easy; 1) setting up new science/research classification system having two dimensions of research and application, 2) building electronic systems and databases allowing fields for several classification systems, and 3) making rules using multi-dimensional classification systems following the purpose of the programs. The model is designed to meet the needs of nationwide R&D and human resources policies, and for the preparation of knowledge society to grasp the relationship between sequential activities using knowledge. If we know the interactive relationships between various areas, we can trace related phenomena in different activities with restricted information.

• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.33-55
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• 2023

There has been research to understand users' information behaviors using book circulation data of public libraries. In this study, we examined the subject areas of books simultaneously borrowed by users of public libraries and aimed to identify the relationships among the subject areas. To accomplish this, we utilized the Korean Decimal Classification codes of 984,790 loaned books in 2019 to transform the lists of concurrently borrowed books, totaling 22,443,699 records, by the same users on the same day, into vectors using the ITEM2VEC technique. Next, we extracted ten highly related classification codes for each classification code, utilizing a total of 522 classification codes to create a network. We identified 15 communities within this network and examined the characteristics of each community. Among the 15 communities, those consisting of two or more main classes allowed us to identify meaningful thematic associations. This study, grounded in users' book usage behaviors, has suggested the topics of books that could be borrowed together. The findings offer valuable insights for library collection development and placement, recommending related subject materials, and revising classification systems.