• 한국문헌정보학회지
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• 제12권
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• pp.201-224
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• 1985

The traditional oriental materials are very important to study on Oriental or Korean studies. Every reseacher that study on this field is familier to Four Category Classification Scheme (四部分類法) as it is based on the traditional knowledge of Orient. Then, when all materials of libraries will he computerized, it will be the first condition that will has to understand about the classification of division and section of oriental knowledge, because not only ancient literature but also many dissertation of this subject will be classified. Therefore, Four Category Classification Scheme has been valuable until now. This paper is intended to help librarians to classify the traditional oriental materials or the dissertation concerned with that, to serve researched user that literatures which have been filed among various traditional bibliographies. The outline of this study are as follows: :1 Examining closely origins, developing process and characteristics of classification of Confacian Classics Part (經部) of Four Category Classification Scheme. (2) Explaning the content of division and section of Confucian Classics Part (經部). (3) Coordinating relation of division and section of Confucian Classics Part as well as those of other parts of the classification scheme. (4) Clearing up the limitation of classification related to other division. (5) Attempting to give basic knowledge on practical classification as concrete examples beloging to each division and section of classification.

• 한국문헌정보학회지
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• 제8권
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• pp.129-155
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• 1981

Four Category Classification Scheme(四部分類法), the traditional classification, is the most proper for classifying the traditional oriental marerials than some other classifications. Therefore, Four Category Classification Scheme has been valuable until now. It is obvious that this classificion aims at a rapid and accurate reference in sorting out the materials and maximun use. This paper is intended as a sludy which helps librarians to classify traditional oriental materials. It is also intended to serve librarians to have easy access to ancient literatures which have been filed among various traditional bibliographies for those who are to research oriental materials as an analysis about Miscelleneous Part(子部). The outline of this study are as follows : (1) Examining closely origins, developing process and characteristics of classification of Miscelleneous Part of Four Category Classification Scheme. (2) Explaining the content of division and section of Miscelleneous Part (子部). (3) Coordinating relations of division and section of Miscelleneous Part as well as those of other parts of the classification scheme. (4) Clearing up the limitation of classification related to other division. (5) Attempting to give basic knowledge on practical classification as concrete examples belonging to each division and section of classification.

• 정보처리학회논문지B
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• 제19B권1호
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• pp.19-26
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• 2012

최근 멀티미디어 정보가 급증함에 따라 콘텐츠 관리에 대한 요구도 함께 증가되고 있다. 이에 오디오 분할 및 분류는 멀티미디어 콘텐츠를 효과적으로 관리할 수 있는 대안이 될 수 있다. 따라서 본 논문에서는 동영상에서 취득한 오디오 신호를 분할하고, 분할된 오디오 신호를 음악, 음성, 배경 음악이 포함된 음성, 잡음이 포함된 음성, 묵음(silence)으로 분류하는 정확도가 높은 오디오 분할 및 분류 알고리즘을 제안한다. 제안하는 알고리즘은 오디오 분할을 위해 서포트 벡터 머신(support vector machine, SVM)을 이용하였다. 오디오 신호의 분류를 위해서는 분할된 오디오 신호의 특징을 추출하고 이를 퍼지 클러스터링 알고리즘(fuzzy c-means, FCM)의 입력으로 사용하여 각 계층으로 오디오 신호를 분류하였다. 제안하는 알고리즘의 평가는 분할과 분류에 대해 각각 그 성능을 평가하였으며, 분할 성능 평가는 정확도율(precesion rate)과 오차율(recall rate)을 이용하였으며, 분류 성능 평가는 정확성(classification accuracy)을 사용하였다. 또한 오디오 분할의 경우는 이진 분류기와 퍼지 클러스터링을 이용한 기존의 알고리즘과 그 성능을 비교하였다. 모의 실험 결과, 제안한 알고리즘의 분류 성능이 기존 알고리즘 보다 정확도율과 오차율 면에서 모두 우수하였다.

• International Journal of Knowledge Content Development & Technology
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• 제7권1호
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 학술대회
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• pp.63-66
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• 1996

In this paper, we propose a new content-based color image retrieval algorithm. The algorithm makes use of two features; colors as global features and block classification results as local features. More specifically, we obtain R, G, B color histograms and classify nonoverlapping small image blocks into texture, monotone, and various edges, then using these histograms and classification results were make a similarity measure. Experimental results show that retrieval rate of the proposed algorithm is higher than the previous method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1373-1387
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• 2012

Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ~ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.449-452
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• 2023

The rapid development of the Internet has led to a significant increase in multimedia content in social networks. How to better analyze and improve video classification models has become an important task. Deep learning models have typical "black box" characteristics. The model requires explainable analysis. This article uses two classification models: ConvLSTM and VGG16+LSTM models. And combined with the explainable method of LRP, generate visualized explainable results. Finally, based on the experimental results, the accuracy of the classification model is: ConvLSTM: 75.94%, VGG16+LSTM: 92.50%. We conducted explainable analysis on the VGG16+LSTM model combined with the LRP method. We found VGG16+LSTM classification model tends to use the frames biased towards the latter half of the video and the last frame as the basis for classification.

• 설비공학논문집
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• 제1권2호
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• pp.162-172
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• 1989

The steady one dimensional heat flow method was used for the measurement of thermal conductivity of kaolin. The effects of the classification, density and moisture content on the thermal conductivity were studied experimentally for the 9 classes of kaolin in Korea. As the results of this study, it was found that the classification did not effect the thermal conductivity, and the conductivity increased as the density and moisture content increased. The correlation equation of the thermal conductivity as a function of the density increase rate was found and the values for the thermal conductivity as a function of moisture content were recommended.

• 한국주거학회논문집
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• 제2권2호
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• pp.41-53
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• 1991

This study discussed the change of housing environmental problems from the early 1900s to the present.The reason is to find the solution of serious housing environment problems. The documentary research method was used for this study.Articles of content analysis(N= 1129)were published in 1920(the first edition)to December. 31, 1990 which were The Dong - A daily news article about housing environment. The main content of this study was examined the change, such as the number of whole article by time series and importance of article(column number of article), classification of article subject, and the number of article by subject. On the basis of this data, was made by chronological classification of the change of housing environment problems for 70 years. Since overall results will become supply of right information about housing environment to fur peoples, will provide the oppronment that oneself ran participate the protection of housing environment, and further will take a part solution of housing environment problems.At the future, I am going to design deep analysis of article content by subject.

• 한국음향학회지
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• 제21권2호
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• pp.182-189
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• 2002

본 논문은 오디오 색인·검색 시스템을 구현하기 위하여 오디오 신호에 대한특징 파라메터 풀 (pool)을 구성하고 이에 따른 오디오 데이터의 내용분석 및 분류에 관한 연구이다. 오디오 데이터는 기본적인 다양한 오디오 형태로 분류되어진다. 본 논문에서는 오디오 데이터의 분류에 이용 가능한 특징 파라메터를 분석하고 추출방법에 대하여 논한다. 그리고 특징 파라메터 풀을 색인 그룹 단위로 구성하여 오디오 카테고리에 대한 설정된 특징들의 포함 정도와 색인기준을 오디오 데이터의 내용을 중심으로 비교 ·분석한다. 그리고 위의 결과를 바탕으로 분류절차를 구성하여 오디오 신호를 분류하는 모의실험을 행하였다.