• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.203-214
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• 1999

본 연구는 A카드 회사에서 현재 실시하고 텔레마케팅 시스템에 데이터마이닝 기법 가운데 하나인 CHAID, CART 알고리즘 및 신경망 기법을 적용하여 모텔을 개발하고 개발된 모델들의 성과를 분석한다. 이를 통하여 어떻게 기업이 데이터베이스와 데이터마이닝 기법을 마케팅에 효과적으로 사용할 수 있는가에 대한 방안을 제시하고 여러 모델들의 성과를 비교 분석하는 방안을 함께 제시한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.203-214
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• 1999

본 연구는 A카드 회사에서 현재 실시하고 텔레마케팅 시스템에 데이터마이닝 기법 가운데 하나인 CHAID, CART 알고리즘 및 신경망 기법을 적용하여 모델을 개발하고 개발괸 모델들의 성과를 분석한다. 이를 통하여 어떻게 기업이 데이터베이스와 데이터마이닝 기법을 마케팅에 효과적으로 사용할 수 있는가에 대한 방안을 제시하고 여러 모델들의 성과를 비교 분석하는 방안을 함께 제시한다.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.360-368
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• 1994

To this day, a number of quantitative analytical methods have been employed in clarifying regional characteristics in the discipline of geography. This paper attempted, as a part of application of those quantitative analyses, to make clear the urban functions and consequently the urban characteristics statistically by adopting newly-introduced CHAID, a sort of discriminant analyis technique. The processing of data was sonducted in two phases. To begin with, the urban functions were classified after designating twenty cities - the population of each city counting 250, 000 or more - as predictor variable, and at the same time four major urban functions like administration, marketing, finance and production as response variable. And then, preeminent functions of individual region were discriminated and concurrently classified by treating the remaining traffic, education, medicare, culture and transportation functions as predictor variable, and the following five regions as response variable: Metropolitan Seoul Area. Pusan region, Taegu region, Kwangju region and Chungcheong region. According to the result of this analysis, marketing and administration are emereed as meaningful functions in Seoul and Taegu respectively. As for the finance function only Pusan and Pucheon can be discriminated. Seoul, Pusan and Seongnam reveal their dominancy in production function. To take a look at the result of the latter analysis, the Metropolitan Seoul area shows, among other functions, strong traffic and finance functions. When it comes fo Pusan region, adminstration, education and finance functions are recorded as a leading ones, and Taegu region is preferable in education, medicare and transportation functions. In case of Kwangju region adminstration, production and education functions are discriminated from any other functions. Chungcheong region shows similar aspect with only traffic function replacing the production function of Kwangju region. Based on aforementioned anlysis, it can be said that the CHAID technique, which is capable of processing large amount of categorical data and, by presenting its outcome in the form of dendrogram, facilitates the interpretation work, is an effective, meaningful means to classify and discriminate certain geographical regions and their characteristics.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.89-101
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• 1999

Increasing number of companies recognize that the understanding of customers and their markets is indispensable for their survival and business success. The companies are rapidly increasing the amount of investments to develop customer databases which is the basis for the database marketing activities. Database marketing is closely related to data mining. Data mining is the non-trivial extraction of implicit, previously unknown and potentially useful knowledge or patterns from large data. Data mining applied to database marketing can make a great contribution to reinforce the company's competitiveness and sustainable competitive advantages. This paper develops the classification model to select the most responsible customers from the customer databases for telemarketing system and evaluates the performance of the developed model using LIFT measure. The model employs the decision tree algorithm, i.e., CHAID which is one of the well-known data mining techniques. This paper also represents the effective database marketing strategy by applying the data mining technique to a credit card company's telemarketing system.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.113-124
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• 2001

CHAID, logistic regression, bagging trees, and bagging trees are compared on SAS artificial data set as HMEQ in terms of classification accuracy and training time. In error rates, bagging trees is at the top, although its run time is slower than those of others. The run time of logistic regression is best among given models, but there is no uniformly efficient model satisfied in both criteria.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.449-459
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• 2015

The purpose of this study was to examine demographic, human capital and service factors affecting employment outcomes of people with hearing impairments. The total of 422 individuals (age from 20 years to 65 years) with hearing impairments were collected from the Panel Survey of Employment for the Disabled from Korea Employment Agency for the Disabled. The dependent variable is employment outcomes. The predictor variables include a set of personal history, human capital and rehabilitation service variables. The chi-squared automatic interaction detector (CHAID) analysis revealed that the status of the national basic livelihood security played a determining role in predicting the employment of people with hearing impairments. Also, it was found that the three factors of the status on the national basic livelihood security, needed help about activities of dailey living, licenses & employment service factors created bigger synergy effect when they inter-complemented one another.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.57-62
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• 2010

Recently, decision tree techniques have been studied in terms of quick searching and extracting of massive data in medical fields. Although many different techniques have been developed such as CART, C4.5 and CHAID which are belong to a pie in Clermont decision tree classification algorithm, those methods can jeopardize remained data by the binary method during procedures. In brief, C4.5 method composes a decision tree by entropy levels. In contrast, CART method does by entropy matrix in categorical or continuous data. Therefore, we compared C4.5 and CART methods which were belong to a same pie using breast cancer data to evaluate their performance respectively. To convince data accuracy, we performed cross-validation of results in this paper.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.328-331
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• 2005

산업재해 통계분석의 커다란 목적은 각 산업별로 주 위험요인을 도출하고 이에 따른 안전교육의 실시 또는 안전장치 등을 보완함으로써 산업재해를 줄이거나 예방하는데 있다고 볼 수 있다. 그러나 일반 제조업이나 건설업 등에서는 아직까지도 정량적 위험성 평가 기법이 개발되어 있지 않은 실정이다. 따라서 효율적인 위험성 평가 기법의 개발이 필요하다. 본 연구에서는 데이터마이닝 기법을 이용한 산업재해 예방을 위한 최적 알고리즘 선정 방법을 제시한다.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.324-327
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• 2005

급속도로 발전하는 산업의 고도화와 이에 따른 업종의 다양화, 이에 동반되는 예상치 못한 산업재해는 불특정 다수에게 인적, 물적 피해를 야기 시키고 있다. 산업재해 예방을 위해 다양한 선행 연구들이 진행되었으나 이들 연구는 기존의 산업재해 데이터를 토대로 빈도분석, 비교분석을 통한 관리적, 교육적 등치 대책만을 제시하고 있다. 본 연구에서는 산업재해 예방을 위해 객관적이고 정량화된 데이터를 통한 예측 분석이 가능한 데이터마이닝을 적용하여 대표적인 기법인 의사결정나무의 CHAID, CART, C4.5, QUEST 4가지 알고리즘 비교분석하여 산업재해 예방 및 전문가 시스템 구축을 위해 적용할 수 있는 최적의 알고리즘을 제시하도록 한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.79-92
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• 2016

The objective of this study is to classify the types of rural areas (138 $si{\cdot}gun$) considering settlement environment by Decision Tree Method (CHAID). The CHAID method was used for decision tree algorithm and the seven dependant variables and 5 explanatory variables were selected, respectively. By decision tree method, rural areas were finally classified into six groups through three separate processes. City area, lower area in aging rate and higher area in farmland area ratio was analyzed to be relatively rich rather than other area in the case of settlement environment index. In the future, this study will be able to utilize as a reference to the planning of rural development projects.