• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.717-724
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• 2005

We often extract a new feature from the original features for the purpose of reducing the dimensions of feature space and better classification. In this paper, we show feature extraction method based on independent component analysis can be used for classification. Entropy and mutual information are used for the selection of ordered features. Performance of classification based on independent component analysis is compared with principal component analysis for three real data sets.

• Journal of Korean Library and Information Science Society
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• v.33 no.1
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• pp.143-167
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• 2002

The aim of this study is to examine the influence of foreign library classification schemes on the Chinese classification systems in the library. And the study is to analyze development process of three modem library classification schemes, the $\ulcorner$Renmin University of China's Library Books Classifications$\lrcorner$, $\ulcorner$Chinese Academy of Sciences's Library Books Classifications$\lrcorner$and $\ulcorner$Chinese Library Classification$\lrcorner$which are being used in many libraries in China where the library is regarded an important organization for performing the national policies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.5-22
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• 2006

A cultural classification and a culture contents industrial classification are the basic tools for cultural policies, cultural supporting, cultural statistics, and evaluations and there is a cyclic processes among them. This study finds out the varieties and short time changes of cultural categorization in laws, statistics, indexes, evaluations, research reports. As a result, colon style new cultural classification is suggested which used networks, media, genre, and cultural comparts as principles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1275-1292
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• 2021

As a fine-grained classification problem, aspect-level sentiment classification predicts the sentiment polarity for different aspects in context. To address this issue, researchers have widely used attention mechanisms to abstract the relationship between context and aspects. Still, it is difficult to effectively obtain a more profound semantic representation, and the strong correlation between local context features and the aspect-based sentiment is rarely considered. In this paper, a hybrid attention capsule network for aspect-level sentiment classification (ABASCap) was proposed. In this model, the multi-head self-attention was improved, and a context mask mechanism based on adjustable context window was proposed, so as to effectively obtain the internal association between aspects and context. Moreover, the dynamic routing algorithm and activation function in capsule network were optimized to meet the task requirements. Finally, sufficient experiments were conducted on three benchmark datasets in different domains. Compared with other baseline models, ABASCap achieved better classification results, and outperformed the state-of-the-art methods in this task after incorporating pre-training BERT.

• Korean Journal of Construction Engineering and Management
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• v.4 no.3 s.15
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• pp.102-111
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• 2003

It is very important to improve the overall efficiency in exchanging construction information among project Parties from the project set-up through the project completion. However, each government agency in Korea tendering construction projects has different structures in classifying information. This results in inefficiency of overall construction projects and cost increasing. This requires establishing a new construction information classification system. This research suggests a framework for an analysis of a standard classification system in setting up a standard classification system and in evaluating its applicability to business processes. According to the identified requirements of the classification system, this research analyzes and compares existing information classification systems such as Uniclass, Uniformat, and Korean Standard Classification System of Construction Information, and then identifies problems and approaches for the improvement.

• ETRI Journal
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• v.21 no.4
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.4
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• pp.361-372
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• 2019

The Overseas Construction Engineering Information System (OVICE), which is operated by the Korea Institute of Construction Technology, uses the Overseas Construction Information Service classification system to service information required for overseas construction of domestic construction engineering companies. In this study, through the application of the recommendation system using collaborative filtering, identifying the relationship between the subjects for real users, verifying the adequacy of the overseas construction information classification system currently in service. Through this, I would like to propose an information service classification system that reflects actual user demand.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.85-87
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• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure and provides useful information for feature selection and extraction. In this paper, we propose a method to predict the classification error for multimodal data based on the Bhattacharyya distance. In our approach, we first approximate the pdf of multimodal distribution with a Gaussian mixture model and find the bhattacharyya distance and classification error. Exprimental results showed that there is a strong relationship between the Bhattacharyya distance and the classification error for multimodal data.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.587-592
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• 2004

Pixel classification is one of basic issues of image processing. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time, a pixel classification scheme based on image information scales is proposed. The proposed method is overcome that computation amount become greater and contents easily get turned. And image directional scales has excellent anti-noise performance. In the result of experiment. good efficiency is showed compare with other methods.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.309-326
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• 2008

NTIS(National Science & Technology Information Service) provides the information for domestic research projects. It in particular has several classification schemes to classify research projects and provide better retrieval and analysis services. It however is difficult to understand the characteristic of a research project clearly since only a classification in a classification scheme can be chosen about a research project. Moreover, the classification scheme covers the high-level classification for every research areas so that it cannot cover the area specialized to the oriental medicines. On the other hand, the classification schemes for oriental medicines have recently been studied in oriental medicine field. However, it also covers the high-level classification for oriental medicine so that it may not suit to a classification scheme for research projects. Therefore, in this paper we propose a classification scheme to understand clearly the characteristic of research projects in oriental medicine and use to use them to retrieval and analysis services.