• 한국조리학회지
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• 제5권2호
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• pp.447-467
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• 1999

Most published work on product quality focuses on manufactured goods. The subject of service quality has received less attention. This distinction is important because some of the quality-improving strategies avaliable to manufacturers may be inappropriate for service firms. Services are performances, not objects. They are often produced in the presence of the customer, as in the cause of hotel restaurant services, quality occurs during service delivery, usually in an interaction between the customer and contact personnel of service firm. for this reason, service quality is highly dependent on the performance of employees, an organizational resource that cannot be controlled to the degree that components of tangible goods can be engineered. The study has begun as a basic study for customer satisfaction-oriented management in understanding the service quality of food & beverage products and through a systematic analysis of it. The major purpose of the study was to examine the relationship of the customer satisfaction and service quality in consideration of reliability, empathy, responsiveness, tangibility and assurance. An empirical research was conducted based on the previous theoretical studies. 286 customer at first class hotels in Seoul were selected as samples of this study. The time period of research was from February through March 1999, and answers were processed by SAS to yield frequency analysis, multivariate statistical analysis and regression analysis. The finding of the statistical treatment are frequencies, factor analysis, multiple regression analysis, path analysis. SERVQUAL method was used the service quality evaluation methods. After factor analysis, it was resulted to 3 factors. those were factor 1(assurance.empathy.responsiveness), factor 2(reliability), factor 3(tangibility). The findings of the statistical treatment are as follows. First, the attribute measurement of performance service quality was affected by customer satisfaction. Second, the attribute measurement of performance service qualify was affected by repurchase intention. Third, The attribute measurement of performance customer satisfaction was affected by repurchase intention. The result of study model was followed, service quality was affected repurchase intention than customer satisfaction. indirected effect through, service duality and customer satisfaction was affected repurchase intention.

• 산업경영시스템학회지
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• 제38권4호
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• pp.45-55
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• 2015

In this paper, we consider curriculum mining as an application of process mining in the domain of education. The basic objective of the curriculum mining is to construct a registration pattern model by using logs of registration data. However, subject registration patterns of students are very unstructured and complicated, called a spaghetti model, because it has a lot of different cases and high diversity of behaviors. In general, it is typically difficult to develop and analyze registration patterns. In the literature, there was an effort to handle this issue by using clustering based on the features of students and behaviors. However, it is not easy to obtain them in general since they are private and qualitative. Therefore, in this paper, we propose a new framework of curriculum mining applying K-means clustering based on subject attributes to solve the problems caused by unstructured process model obtained. Specifically, we divide subject's attribute data into two parts : categorical and numerical data. Categorical attribute has subject name, class classification, and research field, while numerical attribute has ABEEK goal and semester information. In case of categorical attribute, we suggest a method to quantify them by using binarization. The number of clusters used for K-means clustering, we applied Elbow method using R-squared value representing the variance ratio that can be explained by the number of clusters. The performance of the suggested method was verified by using a log of student registration data from an 'A university' in terms of the simplicity and fitness, which are the typical performance measure of obtained process model in process mining.

• 대한영양사협회학술지
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• 제11권4호
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• pp.405-417
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• 2005

The purpose of this study was to evaluate students' satisfaction with foodservice of middle school by region in Gangwon province. Students’ satisfaction concerning foodservice quality characteristics was surveyed by using importance performance analysis(IPA) technique in middle school foodsevice operations. Middle school students from four cities(Gangnung, Sokcho, Wonju, Chuncheon) were surveyed by self-developed questionnaire. Total of 1,025 questionnaires(female 521 and male 504 respectively) were analyzed using SAS program. The results of this study are summarized as follows: 1.The performance level of foodservice quality attributes was significantly different according to region. 2.The attribute of the highest performance level was taste of food. The attributes of the lower performance level were waiting time of meal service and treatment about complaints. The attributes of the higher importance level were hygiene of food and dining room and hygiene of spoon and cup and drinking water table. 3.Satisfied quality attributes identified were taste of food and variety of menu. Dissatisfied quality attribute identified was treatment about complaints. 4.The satisfaction of middle school lunch service was lower than their elementary school period. 5.The satisfied quality attributes of middle school foodservice were portion size, facility of dining room, hygiene of food, variety of menu compared with their elementary school period.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.44-49
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• 2001

This paper is concerned with development of a multi-attribute structured decision model. In this study, we used AHP(analytic hierarchy process) and fuzzy set ranking methodology to overcome the multi-attributes structured decision problems ; such as multi-objective, multi-criterion, and multi-attributes. We proposed a 2-step approach : 1) individual evaluation and 2) integration of individual evaluations. In the first step, we define the performance factors and construct ana]isis structure, and in the second step performance evaluation by individual evaluators, and in second step, the results of individual evaluations are integrate. Also we developed a systematic and practical computer program to solve the problems according to the proposed methods. The proposed approach was known to be effective through a set of sample problems.

• 한국정보과학회논문지:데이타베이스
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• 제28권4호
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• pp.596-605
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• 2001

본 논문은 OLAP에서의 I/O 비용을 줄이는 큐브 계산 방법으로, 구간 기반 큐브 분할 기법을 제안한다. 제안하는 방법은 큐브 분할 단계들 사이에 존재하는 계산의 일부를 중복시켜 처리하는 방법을 통해 큐브 분할 작업의 I/O 성능을 향상시킨다. 계산의 중복을 위하여 제안하는 방법은 애트리뷰트의 단 일 값이 아닌 애트리뷰트 값의 일정 구간을 기준으로 큐브를 분할한다 분석과 실험을 통하여 제안하는 방법의 성능을 기존 큐브 분할 방법과 비교하여 보인다.

• 한국경영과학회지
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• 제32권1호
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• pp.61-75
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• 2007

The purpose of this paper is to develop a new group classification method based on genetic algorithm and to com-pare its prediction performance with those of existing methods in the area of bond rating. To serve this purpose, we conduct various experiments with pilot and general models. Specifically, we first conduct experiments employing two pilot models : the one searching for the cluster center of each group and the other one searching for both the cluster center and the attribute weights in order to maximize classification accuracy. The results from the pilot experiments show that the performance of the latter in terms of classification accuracy ratio is higher than that of the former which provides the rationale of searching for both the cluster center of each group and the attribute weights to improve classification accuracy. With this lesson in mind, we design two generalized models employing genetic algorithm : the one is to maximize the classification accuracy and the other one is to minimize the total misclassification cost. We compare the performance of these two models with those of existing statistical and artificial intelligent models such as MDA, ANN, and Decision Tree, and conclude that the genetic algorithm-based group classification method that we propose in this paper significantly outperforms the other methods in respect of classification accuracy ratio as well as misclassification cost.

• 한국의류학회지
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• 제22권3호
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• pp.374-383
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• 1998

Apparel Quality was one of the most important elements to evaluate the reputations of companies and products which affect the consumer's purchasing behavior. From researches on apparel quality, there was no common concept of quality as well as no common dimensions. The purposes of this study were to identify apparel quality concept and to classify the multi-dimensional concept of apparel quality. The research was carried out in theoretical as well as empirical studies. The theoretical study was conducted to find out apparel quality concept and divide apparel quality concept into four dimensions groups. The empirical study followed the theoretical study to confirm the multi-dimensional concept of apparel quality. The empirical study was investigated that the questionnaire was administered to 634 housewives in Seoul, Kwangju, and Busan during the fall of 1996. The data were analysed by LISREL analysis. This study identified that apparel quality was characteristics of consumer's desires for apparel. The results of the theoretical study verified that apparel quality concept was organized into four different dimensions: physical attribute, physical function, instrumental performance, and expressive performance.

• 한국식생활문화학회지
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• 제38권6호
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• pp.402-414
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• 2023

This study evaluated the consumers' demands and points of improvement for restaurant meal replacement through importance-performance analysis by the restaurant meal replacement segment market using food involvement. The results were as follows. First, after segmenting the restaurant meal replacement market using food involvement, it was classified into three markets (multiple involvements, exploration-oriented, and product quality-oriented). Second, an analysis of the importance of restaurant meal replacement selection attributes revealed taste, sanitation, quality, freshness, price, saving time, texture, ingredients, preparation process, and quantity to be highly important. An analysis of the differences according to the market type revealed the multiple involvement type to be more important than other groups, considering the restaurant meal replacement selection attribute element. Third, an analysis of the importance-performance analysis of restaurant meal replacement selection attributes revealed that quantity and price as the selection attributes that needed to be improved first in all three markets. In addition, in the multiple involvement type, food additives appeared as a selection attribute requiring priority improvement, revealing the characteristics of a market that cares about diet and health.

• 정보처리학회논문지B
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• 제13B권2호
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• pp.133-138
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• 2006

부부분불완전 데이터(Partially Missing Data) 또는 데이터의 속성 값이 표현되는 정도의 깊이가 서로 다른 데이터를 학습하는데 있어서 속성값계층구조(Attribute Value Taxonomy, AVT)를 기반으로 학습하면 기존의 학습 알고리즘을 통해 얻은 결과보다 정확하고 간결한 분류기를 얻을 수 있다는 사실이 밝혀졌다. 하지만 이러한 속성값계층구조는 처음부터 전문가 또는 데이터 도메인에 대한 지식을 가지고 있는 사람에 의해 만들어져 제공되어야 한다. 이러한 수작업을 통한 속성값계층구조를 생성하기 위해서는 많은 시간이 걸리며 생성과정에서 오류가 발생할 수 있다. 또한 데이터 도메인에 따라서 속성값계층구조를 제공할 전문가가 부재한 경우가 있다. 이러한 배경 아래 본 논문은 유전자 알고리즘을 통해 자동으로 근 최적의 속성값계층구조를 생성하는 알고리즘(GA-AVT-Learner)을 제안한다. 본 논문의 실험은 다양한 실제 데이터를 가지고 GA-AVT-Learner로 생성한 속성값계층구조를 다른 속성값계층구조와 비교하였다. 따라서 GA-AVT-Learner에 의해 생성된 속성값계층구조가 정확하고 간결한 분류기를 제공함을 보이고, 불완전데이터 처리에 있어서도 높은 효율을 보임을 실험적으로 증명하였다.

• 한국멀티미디어학회논문지
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• 제6권2호
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• pp.194-207
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• 2003

본 논문에서는 객체 데이터베이스 시스템에서 중포 속성에 대한 색인구조로 다차원 색인구조를 이용하는 다차원 중포 속성 색인구조(Multidimensional Hefted Attribute Index: MD-NAI)의 최적 설계 기법을 제시한다. MD-NAI는 $B^{+}$-tree와 같은 일차원 색인구조를 이용한 중포 속성 색인구조에서 지원할 수 없는 클래스 계층과 중포 속성이 포함된 복합 형태의 질의들에 대한 처리를 잘 지원할 수 있다. 그러나, MD-NAI는 사용자 질의 형태에 따라 색인검색의 성능이 매우 나빠질 수 있다 본 논문에서는 질의 형태에 따른MD-NAI의 성능 개선을 위하여, 먼저 중포 술어에 대한 질의 정보로서 색인 페이지 영역의 최적 모양을 결정하고, 이 최적 모양을 갖는 색인페이지 영역의 모양이 되도록 하는 영역분할 전략을 적용하여 최적의 MD-NAI를 구성한다. 또한, 성능평가를 위하여 MD-NAI를 이용하여 다양한 중포 술어의 형태와 객체 분포에 대하여 실시한 실험 결과를 제시한다. 성능평가의 결과에 의하면, 주어진 질의 패턴에 따라 최적 의 MD-NAI를 구성할 수 있었으며, 삼차원 MD-NAI의 경우에 질의 영역의 구간비가 1:16:256일 때 기존의 순환분할 전략에 의한 MD-NAI에 비해 성능이 5.5배 이상까지 향상되었다.