• Journal of Soil and Groundwater Environment
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• v.15 no.6
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• pp.122-127
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• 2010

Constructing the national inventory that can be used as a tool to identify and assess existing or potential contamination is necessary for efficiently managing the soil and groundwater contamination. In order to start this construction, the first step is how we define and classify potential contamination sources of soil and groundwater. After selecting the basic classification model of contamination sources from developed countries, we suggested the classification and list of the potential contamination sources of soil and groundwater which are appropriate for specific conditions of South Korea. In addition, we investigated several databases to confirm the existence of available data sources and then examined established attribute data through chemical accident response information system (CARIS) and water information system (WIS) in National Institute of Environmental Research and mine geographic information system (MGIS) in Mine Reclamation Corporation. All sorts of attribute data in the existing databases can be utilized as significant assessment factors for determining the management priority of potential contamination sources in the future. Therefore, it is required the expanded investigation of additional database sources and the continual modification so that the classification system of potential contamination sources can be improved.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.103-109
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• 2018

In this paper, we propose a dynamic document classification method which breaks away from existing document classification method with artificial categorization rules focusing on suppliers and has changing categorization rules according to users' needs or social trends. The core of this dynamic document classification method lies in the fact that it creates classification criteria real-time by using topic modeling techniques without standardized category rules, which does not force users to use unnecessary frames. In addition, it can also search the details through the relevance analysis by calculating the relationship between the words that is difficult to grasp by word frequency alone. Rather than for logical and systematic documents, this method proposed can be used more effectively for situation analysis and retrieving information of unstructured data which do not fit the category of existing classification such as VOC (Voice Of Customer), SNS and customer reviews of Internet shopping malls and it can react to users' needs flexibly. In addition, it has no process of selecting the classification rules by the suppliers and in case there is a misclassification, it requires no manual work, which reduces unnecessary workload.

• Journal of the Korean Society for Library and Information Science
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• v.35 no.3
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• pp.17-34
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• 2001

It is very important to organize materials at intemet bookstores. It is time for us to develop a subject classification scheme as a tool for increasing the effectiveness of information retrieval with ease of subject access. The purpose of this study is to examine the subject features of internet bookstores in order to suggest the effective design of the subject scheme for them. Nine internet bookstore websites are analyzed at the aspect of the subject classification of the materials. Based upon the results of this study, an effective subject classification for internet bookstores is suggested to provide a better subject access.

• Journal of the Society of Disaster Information
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• v.9 no.1
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• pp.65-77
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• 2013

There are many institutes which manage the disaster protection resources in their system. The system of the institutes is not mutually compatible, because there is no standard framework of the classification and identification for the disaster management resources. NIMS of FEMA defines the classification and identification framework for the incident resources. All incidents management system of USA including IRIS and webEOC follows the standard resources framework. The aim of the classification and identification of the resources provides the resources list for the disaster and supports to find the resources information efficiently. In this study, we defined the classification and identification of the resources considering the compatibility with the international standard and the field requirements.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.153-162
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• 2009

It is a challenging work for service operators to accurately classify different services, which runs on various wireless networks based upon numerous platforms. This works focuses on design and implementation of a classifier, which accurately classifies applications, which are captured horn WiBro Network. Notion of session is introduced for the classifier, instead of commonly used Flow to develop a classifier. Based on session information of given traffic, two classification algorithms are presented, Classification and Regression Tree and Support Vector Machine. Both algorithms are capable of classifying accurately and effectively with misclassification rate of 0.85%, and 0.94%, respectively. This work shows that classifier using CART provides ease of interpreting the result and implementation.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.207-228
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• 2011

The notes of the classification system are to improve the accuracy and consistency of classification by providing useful information on classification numbers and items. Even though, several notes are used in KDC, they are not enough to keep up with rapidly developing and expanding knowledge of nowadays. The purpose of this study is to suggest appropriate types and improvements of the notes in KDC 5th edition. In order to achieve these purposes, transition of notes in KDC was analyzed. Notes of DDC 23rd edition, NDC new 9th edition, and KDC 5th edition were also analyzed. Based upon these comparison and analysis, problem and improvement of notes in KDC were suggested.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.189-197
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• 2001

Generally, remote sensing is useful to obtain the quantitative and qualitative information of a wide area. For monitoring earth resources and environment, land cover classification of remotely sensed data are needed over increasingly larger area. The objective this study is to propose the process for land cover classification method over a wide area using multi-scene satellite data. Land cover of Korean peninsula was extracted from a Landsat TM and ETM+ mosaic created from 23 scenes at 100-meter resolution. Well-known techniques that used to general image processing and classification are applied to this wide area classification. It is expected that these process is very useful to promptly and efficiently grasp of small scale spatial information such as national territorial information.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.789-816
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• 2019

Text classification is a challenging task, especially when dealing with a huge amount of text data. The performance of a classification model can be varied depending on what type of words contained in the document corpus and what type of features generated for classification. Aside from proposing a new modified version of the existing algorithm or creating a new algorithm, we attempt to modify the use of data. The classifier performance is usually affected by the quality of learning data as the classifier is built based on these training data. We assume that the data from different domains might have different characteristics of noise, which can be utilized in the process of learning the classifier. Therefore, we attempt to enhance the robustness of the classifier by injecting the heterogeneous data artificially into the learning process in order to improve the classification accuracy. Semi-supervised approach was applied for utilizing the heterogeneous data in the process of learning the document classifier. However, the performance of document classifier might be degraded by the unlabeled data. Therefore, we further proposed an algorithm to extract only the documents that contribute to the accuracy improvement of the classifier.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.237-242
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• 2012

Web information service needs a document classification system for efficient management and conveniently searches. Existing document classification systems have a problem of low accuracy in classification, if a few number of feature words is selected in documents or if the number of documents that belong to a specific category is excessively large. To solve this problem, we propose a document classification system using 'Modified ECCD' feature selection method and 'Category Weight for each Document'. Experimental results show that the 'Modified ECCD' feature selection method has higher accuracy in classification than ${\chi}^2$ and the ECCD method. Moreover, combining the 'Category Weight for each Document' feature value and 'Modified ECCD' feature selection method results better accuracy in classification.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.221-247
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• 2013

The purpose of the study is to investigate and analyze the categories of online bookstores and to propose improvements. For the study, the category conformity was compared among eight Korean online bookstores selected; the book classification on the categories was compared from them. The results show that the category conformity was high among online bookstores, but the book classification on the categories was different on the bookstores. ISBN contents classification codes for books might not help to classify the books on the categories. Thus, the study proposes a new publication category for the book classification on categories of online bookstores.