• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.182-189
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• 2002

In this paper, we research the content-based analysis and classification according to the composition of the feature parameters pool for the auditory signals to implement the auditory indexing and searching system. Auditory data is classified to the primitive various auditory types. we described the analysis and feature extraction method for the feature parameters available to the auditory data classification. And we compose the feature parameters pool in the indexing group unit, then compare and analysis the auditory data centering around the including level and indexing criterion into the audio categories. Based on this result, we composed the classification procedure and simulate the auditory data classification.

• Journal of Information Management
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• v.33 no.2
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• pp.19-32
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• 2002

With the growth of the digital library and the use of Internet, the amount of online text information has increased rapidly. The need for efficient data management and retrieval techniques has also become greater. An automatic text categorization system assigns text documents to predefined categories. The system allows to reduce the manual labor for text categorization. In order to classify text documents, the good features from the documents should be selected and the documents are indexed with the features. In this paper, each steps of text categorization and several techniques used in each step are introduced.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.2
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• pp.117-137
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• 2010

The purposes of this study are to review the historical development of food and culture in the KDC (Korean Decimal Classification) and to propose improvements of the KDC to classify materials of food and culture by using the KDC effectively. First of all, changes of classification numbers and headings related to food and culture from the 1st edition to the 5th edition of the KDC were examined. Recent books about food and culture were examined and were classified according to the latest edition of the KDC. Several problems were found including a lack of headings, including notes in food and culture, a lack of headings about Korean foods in particular and reflections about various foods from other countries, a lack of detailed relative headings, and the remaining western oriented headings. Other classification systems about food and culture were analyzed and it was found that there was a need to have new headings for classifying Korean traditional foods and table services, new formats for a relative index, detailed notes, and changes in western oriented headings.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.169-181
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• 2008

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. But, because FNR-tree and MON-tree are stored by the unit of the moving object's segment, they can't support the whole moving objects' trajectory. In this paper, we propose an efficient trajectory index structure, named Trajectory of Moving objects on Network Tree(TMN Tree), for moving objects. For this, we divide moving object data into spatial and temporal attribute, and preserve moving objects' trajectory. Then, we design index structure which supports not only range query but trajectory query. In addition, we divide user queries into spatio-temporal area based trajectory query, similar-trajectory query, and k-nearest neighbor query. We propose query processing algorithms to support them. Finally, we show that our trajectory index structure outperforms existing tree structures like FNR-Tree and MON-Tree.

• Proceedings of the Korean Society for Information Management Conference
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• 1995.08a
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• pp.11-14
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• 1995

기존의 한글 자동 색인 방법들은 어절 단위 색인법과 형태소 단위 색인법으로 분류될 수 있다. 전자는 문서내의 어절에서 색인어의 부분으로서 가치가 없는 음절들을 제거함으로써 색인어를 추출하는 방법으로, 문서에 복합 명사들이 많이 포함되어 있을 경우 검색효과가 저하되는 문제점을 지니고 있다. 후자는 형태소 해석이나 구문 해석을 이용하여 중요한 의미를 갖는 명사나 명사구를 추출하는 방법으로, 단일 명사를 추출함으로써 복합 명사의 띄어 쓰기 문제를 극복할 수 있다. 그러나, 색인 과정에서 요구되는 많은 언어 정보를 개발하고 유지 보수해야 하는 부담을 지니고 있다. 본 논문에서는 기존의 색인 방법들의 문제점들을 완화할 수 있는 새로운 색인 방법을 제안한다. 그리고 실험을 통하여 제안하는 방법의 성능을 평가한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.103-109
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• 2010

As color was used for formative language since a human activity was beginning, all the symptoms in the world that the human eye can see is present. In this paper, we identify Korea traditional color harmony for extracted key frames from scene change detection. Traditional color is classified as 5-Jung-color and 5-Kan-color, and determine whether to harmony. Red, blue, yellow, black, and white, called 5-Jung-color and pink, blue, purple, sulfur, and green, called the 5-Kan-color was identified. First, we extract edge using Canny algorithm. And, we are labeling and clustering colors around the edge. Finally, we identify the traditional color using identification method of traditional color harmony. The proposed study in this paper has been proven through experiments.

• Proceedings of the Korean Society for Information Management Conference
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• 1994.12a
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• pp.125-128
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• 1994

본 연구는 한국도서관학관계문헌색인, 1945-1974와 한국문헌정보학 색인, 1975-1992를 바탕으로 해방 후 48년간의 한국 분류학계가 어떻게 이루어져 왔는지를 연구해 보았다. 이병수, 임종순, 천혜봉, 배영활, 이경호 등에 의해 많은 문헌이 발표되었으며 국립중앙도서관의 도서관에 가장 많은 관련 문헌이 발표되었다. 1970년대 중반 이후로는 대학 논집과 전공학과의 학보에도 많은 문헌이 발행되기 시작하였다. 많은 발전에도 불구하고 외국과 비교해 보면 분류만을 중점적으로 연구하는 연구 단체의 조성과 그 단체가 주축으로 만들어지는 분류 전문 학술지의 발행이 시급하다.

• Proceedings of the Korean Society for Information Management Conference
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• 2001.08a
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• pp.17-22
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• 2001

고유명사의 개념과 판별, 분류체계에 대한 고찰을 통하여 모호했던 고유명사의 기본적인 범주를 분명하게 하였다. 또한, 이러한 분류체계를 바탕으로 문헌정보학에서 고유명사를 색인 및 검색어로 처리할 때 고려 해야할 점에 대해 논하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.120-126
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• 2016

In this study, we propose a method for effectively detecting and recognizing the face in image using RBFNNs pattern classifier and HCbCr-based skin color feature. Skin color detection is computationally rapid and is robust to pattern variation for face detection, however, the objects with similar colors can be mistakenly detected as face. Thus, in order to enhance the accuracy of the skin detection, we take into consideration the combination of the H and CbCr components jointly obtained from both HSI and YCbCr color space. Then, the exact location of the face is found from the candidate region of skin color by detecting the eyes through the Haar-like feature. Finally, the face recognition is performed by using the proposed FCM-based RBFNNs pattern classifier. We show the results as well as computer simulation experiments carried out by using the image database of Cambridge ICPR.