• 한국콘텐츠학회논문지
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• 제17권9호
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• pp.650-660
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• 2017

본 연구는 지금까지의 서사 양식에 등장했던 캐릭터의 성격 유형론을 정리하여, 기존의 캐릭터의 성격 유형론이 갖고 있는 문제점을 정리하고 새로운 분류 가능성을 제안하기 위한 것이다. 지금까지 서사 이론에서 캐릭터 유형의 분류는 크게 서사 내에서의 역할이라는 형식적인 분류와 인간의 내적 자질에 근거한 내용적인 분류, 그리고 그 두 가지 분류 기준이 착종된 보완적 분류로 이루어져 있었다. 기존 캐릭터 분류 유형이 담고 있는 문제는 바로 인간의 내적 자질에 근거한 내용적인 분류의 유용성에 비해 실질적으로 분류가 어렵다는 점이다. 반면 서사 내 등장인물의 역할에 따른 분류는 그 분류가 형식적이기 때문에 서사론의 발전상 중요하게 다뤄져 왔지만, 그다지 실질적인 분석 방법론으로 기능하기는 어려웠다. 본 연구는 이러한 문제를 해결하기 위한 시론적인 성격으로, 샬롬 슈워츠의 인간의 가치 유형을 도입하여, 인간의 가치 유형과 인간의 역할을 상호 관련시켜 새로운 캐릭터 분석 방법의 가능성을 제안하고자 한다. 슈워츠의 가치 유형 연구는 인간의 행동의 동기를 파악하는 데 매우 효과적인 방법론으로, 등장인물의 지향성을 분석하는 데 큰 의미가 있을 것이다.

• 한국도서관정보학회지
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• 제15권
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• pp.113-151
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• 1988

The enumerative classification schemes do not represent the tiny mass of knowledge embodied in a article in a periodical or in a chapter or a paragraph of a book. But today's information centers regard a tiny spot of knowledge embodied in a article as a class. we call this micro-thought. But the enumerative classification are manual systems, it cannot be a n.0, pplied to the automation of classification. The purpose of this study is to build a general principle for the automatic book-classification which can be put to use in library operation, and to present a methodology of the automatic classification for the library. The methodology used is essentially theoretical, Published works by and about Ranganathan, especially 6th edition of the CC were studied, analyzed. The principle of automatic book classification derived from the analysis of colon classification and facet combinations. The results of this study can be summarized as follows ; (1) This study confined the fields of library science and agriculture. (2) This study represent a general principles for the automatic book classification of library science and agriculture. (3) Program flowcharts are designed as a basis of system analysis and program procedure in library science and agriculture. (4) The principles of the automatic classification in library, science is different from that of agriculture. (5) Automatic book classification can be performed by the principle of faceted classification, by inputting the title and subject code into a computer. In addition, the expected value from the automatic book-classification is as follows (1) The prompt and accurate of classification is possible. (2) Though a book is classified in any library, it can have same classification number. (3) The user can retrieve the classification code of a book for which he or she wants to search through dialogue with the computer. (4) Since the concept coordination method is employed, a tiny mass of knowledge embodied in a article in a periodical or in a chapter or a paragraph of a book can be represented as a class. (5) By performing automatic book-classification, the automation of library operation can be completed.

• 한국한의학연구원논문집
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• 제3권1호
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• pp.153-167
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• 1997

Conventionally, identification and classification methods of natural products include the morphological survey and assay of chemical disposition, sing these methods, however, is not satisfying for the precise identification of natural products because they are often valiable in the compositions and morphology To standardize the natural products identification and classification, genomic DNA analysis such as RAPD, RFLP and Amp-FLP can be adopted for this purpose. In this study, various ginsengs and bear gall bladder were tested for the development of genetic identification and classification method. Varieties of ginsengs such as, P. ginseng, P. quinquefolium, P. japonicus and P. notoginseng, were genetically analyzed by RAPD. Also, DNA isolated from Bear blood and gall bladder, Ursus thibetanus, Ursus americanus and Ursus arctos, were analyzed by the same method. The results demonstrated that the identification and classification of bear gall bladder and various ginsengs were possible by RAPD analysis. Therefore, this method was thought to be used as a additional method for the identification and classification of other natural products.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.403-413
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• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• 품질경영학회지
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• 제30권1호
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• pp.152-161
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• 2002

The analysis of large data sets with hundreds of thousands observations and thousands of independent variables is a formidable computational task. A less parametric method, capable of identifying important independent variables and their interactions, is a tree structured approach to regression and classification. It gives a graphical and often illuminating way of looking at data in classification and regression problems. In this paper, we have reviewed and summarized tile methodology used to construct a tree, multiple trees and the sequential strategy for identifying active compounds in large chemical databases.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.205-208
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• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers devote their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new classification method for remote sensed image data that use rough set theory. Using indiscernibility relation of rough sets, we show that can classify image data very easily.

• 한국의류학회지
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• 제40권2호
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• pp.287-304
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• 2016

This study examines the influence of product classification standards and structure on user perception as well as their attitude towards online shopping sites. The causal relationships of variables are also examined. The analysis was based on an online survey with 247 responses. Four types of internet shopping sites were developed and used as a stimulus. The results of the mean comparison analysis indicated that perceived variety, information overload, perceived shopping value and attitude towards the site varies significantly with product classification standards and structure. There was also of a marginally significant interaction between the classification standard and structure on perceived variety and information overload. The causal relationship analysis revealed that perceived variety positively influenced hedonic and utilitarian shopping value. However, information overload had a negative effect on hedonic and utilitarian shopping value. Both the hedonic and utilitarian shopping value positively influenced attitudes towards the sites. This study demonstrates that classification method influences customer perception and attitude. It offers interesting insights on a product classification method as a strategic tool for online shopping.

• 한국안전학회지
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• 제34권5호
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• pp.119-131
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• 2019

Among the themes for CSR(Corporate Social Responsibility), consumer issues include protecting the health and safety of consumers who purchase and use the products. In particular, ensuring product safety is a major theme of consumer issues for corporate social responsibility. Currently, the government implements the Electrical Appliances and Consumer Products Safety Control Act for product safety management and selects products that may harmful to consumers as safety control items, and manages the products by designating them as 4 types of safety certification, safety confirmation, supplier conformity verification, and safety standard compliance. In this paper, we propose management plans for the establishment of a more reasonable classification type of safety management target for 48 items of consumer products to be controlled by the act, and confirm the validity of the plan. First, we perform cluster analysis using data for CISS (Consumer Injury Surveillance System) to derive a new classification type of the safety management target. Next, we compare the results of the cluster analysis with the classification type of the act and the existing scenario classification method RAS (Risk Assessment by Scenario) and the causal network method RAMP (Risk Assessment Method based on Probability). Based on these results, we propose two new plans of safety management target classification and verify its validity.

• 대한의용생체공학회:의공학회지
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• 제43권2호
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• pp.109-115
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• 2022

Purpose: Medical records classification using vectorization techniques plays an important role in natural language processing. The purpose of this study was to investigate proper vectorization techniques for electronic medical records classification. Material and methods: 403 electronic medical documents were extracted retrospectively and classified using the cosine similarity calculated by Scikit-learn (Python module for machine learning) in Jupyter Notebook. Vectors for medical documents were produced by three different vectorization techniques (TF-IDF, latent sematic analysis and Word2Vec) and the classification precisions for three vectorization techniques were evaluated. The Kruskal-Wallis test was used to determine if there was a significant difference among three vectorization techniques. Results: 403 medical documents were relevant to 41 different diseases and the average number of documents per diagnosis was 9.83 (standard deviation=3.46). The classification precisions for three vectorization techniques were 0.78 (TF-IDF), 0.87 (LSA) and 0.79 (Word2Vec). There was a statistically significant difference among three vectorization techniques. Conclusions: The results suggest that removing irrelevant information (LSA) is more efficient vectorization technique than modifying weights of vectorization models (TF-IDF, Word2Vec) for medical documents classification.

• 동의생리병리학회지
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• 제18권6호
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• pp.1938-1944
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• 2004

In this study, when we make a diagnosis of constitution using QSCC Ⅱ(Questionnaire of Sasang Constitution Classification). data mining techniques are applied to seek the classification function for improving the accuracy. Data used in the analysis are the questionnaires of 1051 patients who had been treated in Dong Eui Oriental Medical Hospital and Kyung Hee Oriental Medical Hospital. The criteria for data cleansing are the response pattern in the opposite questionnaires and the positive proportion of specific questionnaires in each constitution. And the criteria for variable selection are the test of homogeneity in frequency analysis and the coefficients in the linear discriminant function. Discriminant analysis model and decision tree model are applied to seek the classification function into Sasang constitution. The accuracy in learning sample is similar in two models, the higher accuracy in test sample is obtained in discriminant analysis model.