• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1137-1143
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• 2011

The purpose of this paper is to analyse the preference for direct marketing according to the characteristics of policyholders and suggest implications for marketing strategies with regard to direct marketing. A marked characteristic of this paper is a good quality of data and the results gained from analysing the data can be trusted very much. Binary logistic regression is employed. A statistically significant preference is shown in the group such as male, a younger generation, a hazardous occupation, the metropolitan area, and the customer of foreign company. The results suggest that promotion for female is needed to revitalize direct marketing. A tight underwriting for a hazardous occupation is also required.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.642-644
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• 2014

정보의 폭발적인 증가로 인해 사용자들은 오히려 원하는 정보를 빠른 시간에 얻는 것이 힘들어졌다. 따라서 이 문제를 해결하기 위한 다양한 방식의 새로운 서비스들이 제공되고 있다. 추천 시스템 중에서 영화를 추천해주는 방법에는 사용되는 알고리즘에는 협업필터링 방법이 가장 성공한 알고리즘으로 사용되고 있다. 협업 필터링 방법은 사용자가 자발적으로 입력한 선호도 평가치를 바탕으로 추천 하고자 하는 사용자와 취향이 비슷하다고 판단되는 사람들 즉, 최근접 이웃을 구하고 최근접 이웃의 선호도 평가치를 바탕으로 사용자에게 영화를 추천을 해주는 기법이다. 그러나 협업 필터링에는 몇 가지 대표적인 문제점이 있으며 희박성 및 확장성, 투명성이 있다. 본 논문에서는 영화 추천 시스템에서의 협업필터링의 희박성 문제를 보완하고자 개개인의 성향을 반영하여 효율이 좋은 추천 방법을 제안하고 하둡에서 성능평가를 하였다.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.319-329
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• 2018

With rapid development of technology for strong AI chatbot, the role of chatbot has been extended from conducting simple tasks to being a friend or counsellor. For this newly emerging purpose of chatbot, endowment of personality is important to make the chatbot regarded as a human being. Nevertheless I found that there are few guides about it. Thus, this study identifies the proper personality of chatbot depending on the purpose of services and user types. The purposes of chatbot services are divided into three types such as leisure-time, counselling, and task. The DISC theory is used for categorizing personality, which consists of 4 types such as dominance(D), inducement(I), submission(S), and compliance(C). An interview and survey were conducted to investigate the preferred personality of chatbot and contents for leisure-time. As results, people tend to prefer people-oriented types such as I, S for their leisure time, task-oriented types such as D,C for their task, and slow types such as C,S for counselling. Women prone to prefer neutral gender except for counselling and men tend to prefer female in all chatbot services. Preferred chatbot age is either same or younger age for leisure-time, same or older for counselling, and 30's for tasks. Preferred contents for leisure-time are mostly recent information but many 20's want fun contents and 50-70's want emphatic conversation. 30-50's want honorific but 20's and 60-70's don't care. The research results useful guide on proper personality of AI chatbot for each purpose of its service.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.69-80
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• 1986

In order to analyse the color preference quantitatively, specially with reference to the subjects in the age of twenties, 100 subjects(M=50, F=50) that unconsidered other factors were adopted and responded to 4 items of the questionaire. The item no. 1 was to investigate the most prefered color on the white background, no. 2 was to most preferred stimulation -level of lightness in the same hues, no. 3 was to most prefered color on 5 different backgrounds -grey, blue, pink, yellow, and yellow green-, and no. 4 was same as no. 3 but with different color-arrangement Materials for item 1 and 3 were made with transparent acryl-boards(30cm$\times$30cm), on which 16 color chips arranged on circle, for item 4 on lattice, and for item 2 with 16 white boards(8cm$\times$21cm), on which 7 color chips of different lightness-level arranged. Reflectance(Y) and color coordinate(x, y) of all color chips measured with color difference meter were transfered into wavelength(nm), exitation purity(%), and Munsell's value. The results may be summarized as follows: 1) Most prefered color was bluish green with wave1ength about 500nm. As increasing of exitation purity of color, more prefered. 2) When there were 7 different levels of lightness in the same hues, the relationship between the number of preference and the stimulation was inverted U-shaped. 3) With changing the background -color, the prefered colors were contrasting when backgrounds were low or high intensity-stimulation and familiar colors when backgrounds were medium intensity.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.71-79
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• 2004

Owing to the rapid increase of the number of automobiles, the traffic is being heavily crippled as time goes by. To provide drivers with better safety and convenience, a variety of CNSs(Car Navigation System) are being installed more and more specially for the vehicles which are produced in recent days. As the CNS has gained the public popularity, it has been playing a role as a component of the multimedia system in a vehicle in addition to providing the capability of route guidance service. It is, therefore, now recognized as an important unit of the vehicle interior system. As the situation has been changed as formerly described, it is necessary that not only the functions but also the usability and exterior features are to be designed to suit customers' tastes. This paper is an attempt to find out what the major sensibility factors which customers want as far as a CNS is concerned are. Because these factors can differ from a vehicle type to another that customers prefer, the analysis is based on the vehicle preference. It is proved that MDS(Multi Dimensional Scaling) is an effective method to analyze the sensibility factors for the different types of vehicles. The result shows that for the people who prefer the sedan-type vehicles, luxuriousness, harmoniousness, and texture are major factors. For people who like sports car, faminism, salience, and dynamics are major factors. For people who prefer SUV's(Sports Utility Vehicle) or MPV's(Multi Purpose Vehicle), solidity, dynamics, and convenience are important.

• Bio news
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• no.5
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• pp.29-29
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• 2004

• Monthly Korean Chicken
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• v.50 no.44 s.110
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• pp.84-91
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• 2004

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.107-121
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• 2004

Although consumer needs for better products force manufactures to put emphasis on design, often development of a product has been done without the formal phase to consider human needs. In order to identify the implicit needs of customers and the areas of potential demand on a product, several analysis scheme such as QFD(quality function deployment) has been developed. For this, first of all, the methods for evaluating consumers satisfaction about their needs must be determined. However there were only few systematic methods on shoe design. In this paper we developed an innovative framework for human satisfaction evaluation of shoes. As a result, we uncovered 29 dominant human satisfaction dimensions for customer-oriented quality evaluation of a comfortable shoes. Here, 29 satisfaction dimensions were identified as the dimensions that represent the human sensitivity and psychological feeling on comfortable shoes. This study helped the designers and developers clarify the conceptual and abstract aspect of the design evaluation by proposing a more systematic and process-oriented method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.160-166
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a user preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or ron-spam in a meaningful way. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.443-450
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• 2005

In this paper, we propose an intelligent model lot extraction of the web user's preference and present the results of evaluation. For this purpose, we analyze shortcomings of current information retrieval engine being used and reflect preference weights on learner. As it doesn't depend on frequency of each word but intelligently learns patterns of user behavior, the mechanism Provides the appropriate set of results about user's questions. Then, we propose the concept of preference trend and its considerations and present an algorithm for extracting preference with examples. Also, we design an intelligent model for extraction of behavior patterns and propose HTML index and process of intelligent learning for preference decision. Finally, we validate the proposed model by comparing estimated results(after applying the Preference) of document ranking measurement.