• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.87-93
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• 2012

This paper discusses a new weighting method for text analyzing from the view point of supervised learning. The term frequency and inverse term frequency measure (tf-idf measure) is famous weighting method for information retrieval, and this method can be used for text analyzing either. However, it is an experimental weighting method for information retrieval whose effectiveness is not clarified from the theoretical viewpoints. Therefore, other effective weighting measure may be obtained for document classification problems. In this study, we propose the optimal weighting method for document classification problems from the view point of supervised learning. The proposed measure is more suitable for the text classification problem as used training data than the tf-idf measure. The effectiveness of our proposal is clarified by simulation experiments for the text classification problems of newspaper article and the customer review which is posted on the web site.

• 대한전기학회논문지:전력기술부문A
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• 제53권9호
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• pp.513-520
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• 2004

In the paper, we summarize the result of the experimental research for the overload criteria of domestic distribution transformers considering the electric consumption patterns of customers. For the basic characteristic data of distribution transformer overload, the actual experiments are accomplished. The field data of loads are surveyed from sample transformers for analyzing the consumption pattern of customer load. The load data acquisition devices are equipped, and the algorithm of load pattern classification is applied. In addition to this efforts, various load pattern data. in past are gathered. Then the representative load pattern of each customer type in domestic is extracted. The final results of overload criterions are presented as tabular form through the results of experiments and survey are combined. The field test of the experiment results is peformed using the special manufactured transformers, which can measure both the load and top-oil temperature of transformer. Through this, we verify that the results of field test are similar to the laboratory one and the Proposed overload criteria can be effectively applied to the real system.

• 한국정보시스템학회지:정보시스템연구
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• 제18권3호
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• pp.375-399
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• 2009

In this study, we propose a integrated model of logistic regression, artificial neural networks, support vector machines(SVM), with case-based reasoning(CBR). To predict respondents in the direct marketing is the binary classification problem as like bankruptcy prediction, IDS, churn management and so on. To solve the binary problems, we employed logistic regression, artificial neural networks, SVM. and CBR. CBR is a problem-solving technique and shows significant promise for improving the effectiveness of complex and unstructured decision making, and we can obtain excellent results through CBR in this study. Experimental results show that the classification accuracy of integration model using CBR is superior to logistic regression, artificial neural networks and SVM. When we apply the customer response model to predict respondents in the direct marketing, we have to consider from the view point of profit/cost about the misclassification.

• International Journal of Quality Innovation
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• 제2권2호
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• pp.58-68
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• 2001

This paper proposes a method for quantifying the types of quality elements proposed by Kano; namely: attractive quality, one-dimensional quality, and must-be quality. Kano's classification of required quality has helped us improve our thinking in product development. However, his classification is conceptual rather than quantitative, and the conventional techniques of questionnaire and group interview cannot provide quantification of the relationship between the degree of customer satisfaction and the degree of sufficiency of required qualities. This paper describes how a quality element under Kano's quality model can be expressed as a utility function, and describes an application to quality design of a cellular phone.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 춘계학술대회 논문집
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• pp.305-314
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• 2002

In order to adapt to today's rapidly changing environment and gain a competitive advantage, many companies are interested in CRM(Customer Relationship Management). Especially, the product recommendation system that can be implemented by personalizing the marketing strategy becomes the focus of CRM. In this research, we employed CBR(Case-Based Reasoning) technique that can overcome the limitation of CF(Collaborative Filtering) technique. Our system recommends the books that the customer is very likely to buy next time considering the factors such as 'Personal Features of Customer,' Similarity between Book Categories' and 'Sequence of Book Purchases'. Accuracy of predicting a book-not a particular book, but in the middle level of classification that contains about 190 categories-was about 57%.

• 한국조리학회지
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• 제7권2호
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• pp.1-24
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• 2001

A Study on the strategic methods for internal marketing of Family Restaurant. We know that customer satisfaction in measuring the effect of marketing performance on employees in service industry. There are four strategies of internal marketing for service-employee, which are participation-promotion and manner-management of employee, classification to employee, communication strategy, motivation environment for employee. First, communication, sales and service technology of employee can be developed and improved through the education and training. Second, company can make better achievement by classifying life-style and individual desire. Third, communication strategy can improve service quality by development of team-work through the confidence and joint-responsibility. Fourth. the company make environment which employee can compete by offering incentive fairly and properly. In the conclusion, when employees serve customers in a depressed attitude, they neglect service process and bring about customer non-satisfaction. This have negative effect on external customer satisfaction in the short term. And so that customer-satisfaction can't exist without employee-satisfaction. that is job-satisfaction is the goal of company. therefore study about internal marketing action should be go on.

• 마케팅과학연구
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• 제14권
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• pp.125-144
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• 2004

본 연구는 중소규모의 인터넷 전자상거래쇼핑몰의 소비자정보 최적화를 위한 마케팅모듈의 적용에 관한 연구이다. 본 연구에서 적용한 마케팅모듈은 e-CRM 의 RFM 모듈과 이메일에 대한 장기적인 고객반응도를 분석한 이메일 반응모듈이며, 이 두 가지 분석방법으로 분류된 소비자그룹에 대한 이메일발송을 통한 ROI 분석을 통해 마케팅모듈에 대한 타당성을 검증하고자 하였다. 연구결과 두 가지 모듈에 의해 분류된 각 그룹에 대한 ROI 분석결과 매출에 대한 기여도인 전환율, 개인화요소 및 이메일반응점수인 충성도지수 모두 우수고객이 타 고객에 비해 높은 것으로 나타났으며, 이메일 기초반응도인 오픈율, 인지율, 클릭율에서도 접수가 높은 것으로 나타났다. 따라서 자본, 인원의 제약이 따르는 중소 인터넷기업은 저비용, 고효율의 타겟 마케팅 전략으로서 유효DB를 확보해야 하며, 기업의 DB구조 및 특성에 따라 RFM 및 이메일반응 모듈과 같은 타당한 마케팅모듈을 채택하여 고객서비스 및 기업수익을 강화할 수 있을 것이다.

• 한국의상디자인학회지
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• 제4권3호
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• pp.33-42
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• 2002

The purpose of this study was to find out criteria for classifying fashion brand from consumer point of view in order to develop strategy of fashion brands and to manage brand effectively and systematically, and to suggest theoretical frame for application of these criteria. Survey was used as a research method. Subject were 422 age of 20-30 women living in and near Seoul. Questionnaires was developed to based on 37 classification criteria, and SPSS package program were used to analyze data. The results of this study were as follows: First, factor analysis considering 37 classification criteria identified 8 factors as classification criteria. They were the level of brand form, the level of product concept, the level of management item, the level of brand sales ability, the level of customer management, the level of brand advertizing and awareness, the level of brand value, the level of product lead ability. Second, the most important factor was the level of customer management, but comparatively factor of the level of brand sales ability the level of brand value was less important. Third, consumer cognized difference of criteria for classifying fashion brands. And the level of product lead ability was the most important factor in women's wear category and the level of brand form was in general casual wear category.

• 한국주거학회:학술대회논문집
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• 한국주거학회 2008년 추계학술발표대회 논문집
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• pp.327-331
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• 2008

In Korea, welfare needs brought on by the rapidly growing of elderly population. Also, the senior group with spare time, wealth and health is increasing. Currently, the people have known about needs welfare system for improving quality of life during senescence personally and socially. In addition to the senior friendly industry, having distinction with simple approach medical services, will be great expanding after 2010. And there will be a new welfare services plan supporting long term care insurance for senior citizens. But we don't have prepared systematically organized senior friendly industry and products yet. So, the purpose of the study is to analyze systematically the classification characteristics of the senior friendly products according to the difficulty of daily living for senior citizens. Above all, the study finds out the senior friendly products characteristics according to the consumer's various situations about health and housing space. Therefore the result of the study reveals that the simulation guidelines for choosing the products depend on the customer's needs are essential and useful to improve senior friendly industry. And the post evaluation data of senior friendly products would be put to practical use in the industry.

• KEPCO Journal on Electric Power and Energy
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• 제2권1호
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.