• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.151-167
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• 2019

Korea's current Land Category Classification System(LCCS) can not accurately register of complex and diverse Status of land use in Cadastral Record. Therefore, in order to draw implications for the improvement of LCCS in Korea, Shin SW and four others published a paper titled 'A Study on Land Category System of Domestic and Foreign Country' in 2013. This paper compared the 'land category', 'land use' and 'land cover' of six countries on the same line, and Some non-factual content was described. So, presented a new perspective on this. Looking forward, I hope that reasonable alternative will be presented based on the understanding of LCCS of Germany, Japan and Taiwan. In the future research project, to study the history of LCCS in Germany and Taiwan and suggest to refer to improvement of LCCS of Korea.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1150-1155
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• 2009

In the information society, the amount of information have been increased by technological development. It is not easy to deal with information for fast data processing because of increasing of the complexity and diversity of data. So this paper will confirm the fact that the color plays the role of the classification of complex information and can make data processing fast. Experiment 1 shows that the searching time of target(line name) is more faster when the color of a subway line is equal to the color of station`s name. Experiment 2 using the task for classification of word mixed in various categories shows that color category processing is more faster rather than semantic category processing and the effect of this task is far better when color difference is more clear.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• Research in Community and Public Health Nursing
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• v.12 no.2
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• pp.513-531
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• 2001

Television news programs are becoming significant source of health information. This study aims at investigating the current state of health coverage of the prime time news program in Korea. Data were collected from KBS 9 0'clock news in the period of thirteen months. from December 1. 1998. to November 1. 1999. The data were analyzed using content analysis method. and the reliability degree was 99.7% according to the Holsti's inter-coder reliability test. The current research classified 489 health related news items into 49 sub-categories and five health categories through content analysis. Some of the basic results of this study are as follows. 1. The frequency according to health category, health maintenance promotion(57.3%) topped followed by disease prevention(23.2%), disease treatment(14.9%), life ethics(4.0%), and growth development(0.6%). 2. According to human developmental age. for the most part(80.1 %) is applicable to the entire range of human developmental age. 3. Health maintennance promotion category take top of health category by the rate of 57.3% and contain 20 sub-categories. 4. News items in the life ethics category, which had six sub-categories. occupied only four percent of the total health related news. News in the growth development category included two sub categories and occupied 0.6% of the total news items. 5. In disease prevention and disease treatment category, infectious disease(33.2%) showed the highest percentage according to the WHO's international disease classification system. Disease prevention occupied 23.2% and contained eleven sub-categories while disease treatment occupied 14.9% and included ten sub-categories. Television news coverage on health showed a wide variety of selection in terms that they are reporting various issues. This study, however, found that some news items were confusing and failing in presenting scientific evidences. It is suggested that the television coverage on health could be beneficial to most of viewers in receiving important health information and guidelines, only if they are utilizing their own sound discretion in consuming those news.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.733-741
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• 2012

In recent, many consumers visit the online shopping malls or price comparison sites to collect the information on the product category that they are interested in. However, the volumes of the data provided by such web sites are often too enormous, and significant number of consumers have trouble in making purchase decision based on the plethora of products and sellers. In this context, modern online shopping agents need to process the retrieved information in more intelligent way before providing them to the users. This paper proposes a novel approach for identifying the main price ranges hidden in a single product category. To this end, the price of an item in the category is represented as a row vector and k-means clustering analysis is applied to the price vectors to produce the clusters that consists of the product items with similar price vectors. Then, the main price ranges of the product category can be identified from the result of clustering analysis. In general, the price is one of the most important factors in the consumers' purchase decision, and the identified main price ranges will be helpful for the online shoppers to find appropriate items effectively.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.10-24
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• 2006

Performing a survey on the employers of S company that have built an EIP and used it effectively, we examined the priority of success factors that are considered as important ones by managers, general users, and system administrators. Then, we examined whether the priorities are different among the users of EIP according to the job, position, and period of use. Further, we looked into how the past and present EIP system of S company implemented the factors that took the first and the second places in priority for each of the four categories; the category of factors considered at the in of determining whether to build the system, the category of system functions provided in general, the category of functions provided with high priority when the system is used after the building, md the category of factors that make effective use of the system once it is built.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.294-301
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• 2004

·Text-mining approach to e-documents organization based on topic hierarchy - Machine-Learning ＆ information Theory-based ㆍ 'Category(topic) discovery' problem → document bundle-based user-constraint document clustering ㆍ 'Automatic categorization' problem → Accelerated EM with CU-based active learning → 'Hierarchy Construction' problem → Unsupervised learning of category subsumption relation

• Korean Journal of Mathematics
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• v.22 no.4
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• pp.693-698
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• 2014

Although the category NFHG of normal fuzzy hypergroups is not a topos, it forms a pseudo topos. Also we show that there are pseudo power objects in NFHG.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.283-304
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• 2008

This is to develop Intelligent Retrieval System which can automatically present early query's category terms(association terms connected with knowledge structure of relevant terminology) through learning function and it changes searching form automatically and runs it with association terms. For the reason, this theoretical study of Intelligent Automatic Indexing System abstracts expert's index term through learning and clustering algorism about automatic classification, text mining(categorization), and document category representation. It also demonstrates a good capacity in the aspects of expense, time, recall ratio, and precision ratio.