• 한국유통학회지:유통연구
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• 제12권2호
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• pp.103-129
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• 2007

마케팅 사상사에서 지금까지 지속되고 있는 중요한 개념 중의 하나는 소비재의 분류에 관한 것이다. Copeland(1923)가 최초로 제안한 상품분류방식과 이론은 지금까지 거의 수정되지 않은 채 학계와 실무자들이 원용하고 있고 미국 마케팅 협회를 비롯한 유관기관들도 이를 공식적으로 인정하고 있다. 그러나 그의 분류방식은 오늘날에는 시대에 뒤떨어진 낡은 것이 되어 현대의 상품광고, 소매업 및 소비에 적절하지 않은 것으로 점차 알려지고 있다. 그러한 방실은 특히 현대사회에서 소비자들이 스타일, 개인적 정체성 및 사회적 지위나 신분에 집착하고 있음으로 인하여 소비자 시장을 잘 이해하고 있는 브랜드 관리자들이 중점적으로 촉진하고 있는 상품의 사회적 특성이 소비자의 선택과 구매자 행동의 핵심적 결정요인이라는 사실을 수용하지 못하고 있다. 이에 따라 본 연구자는 기존의 상품분류방식이 다년간 시장조건의 변화에 대응하지 못하고 있는 이유를 탐구하고 그것이 소비와 소비자행동에 영향을 미치는 다수의 요인들을 반영하지 못하고 있다는 것이 가장 중대한 약점임을 주장하였다. 한걸음 더 나아가 기존의 연구문헌을 토대로 그러한 약점을 극복할 수 있는 새로운 상품분류방식을 제안하였다.

• Journal of applied mathematics & informatics
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• 제3권2호
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• pp.117-128
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• 1996

Complementation theory in krein spaces can be extended for any self-adjoint transformation. There is a close relation between Julia operators and linear systems. The theory of Julia operators can be used to construct distinct Krein spaces which are the state spaces of extended canonical linear systems with given transfer function.

• 경영과정보연구
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• 제1권
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• pp.401-412
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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 have been devoted their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new bands selection method for multispectral bands of remote sensed image data that use rough set theory. Using indiscernibility relations in rough sets, we show that can select the efficient bands of multispectral image data, automatically.

• Journal of the Korean Statistical Society
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• 제36권3호
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• pp.367-372
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• 2007

Classification as a tool to extract information from data plays an important role in science and engineering. Among various classification methodologies, support vector machine has recently seen significant developments. The central problem this paper addresses is the accuracy of support vector machine. In particular, we are interested in the situations where fast rates of convergence to the Bayes risk can be achieved by support vector machine. Through learning examples, we illustrate that support vector machine may yield fast rates if the space spanned by an adopted kernel is sufficiently large.

• Communications for Statistical Applications and Methods
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• 제2권1호
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• pp.74-88
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• 1995

This article introduces a unified method of choosing the most explanatory and significant multiway partitions for classification tree design and analysis. The method is derived on the impurity reduction (IR) measure of divergence, which is proposed to extend the proportional-reduction-in-error (PRE) measure in the decision-theory context. For the method derivation, the IR measure is analyzed to characterize its statistical properties which are used to consistently handle the subjects of feature formation, feature selection, and feature deletion required in the associated classification tree construction. A numerical example is considered to illustrate the proposed approach.

• 한국학교ㆍ지역보건교육학회지
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• 제6권
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• pp.117-126
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• 2005

This study attempted to extract a suggestive point to help the design of a program, which is used to promote physical activities, by applying a social cognitive theory based on literature review on the physical activity based on a social cognitive theory. This study considers 10 journal articles that used a social cognitive theory, physical activity, and exercise as the major variable using the EBSCOhost Academic Search Premier and Educator's Reference Desk (ERIC). The type of papers was analyzed using a certain criterion, which can be configured according to the number of each year's papers, characteristics of research subjects, application type of a social cognitive theory, and classification of the application of objects in a social cognitive theory. The characteristics of each year's papers presented no specific characteristics for each year's papers, but the study in 2004 especially presented a high level. The characteristics of research subjects presented four highest cases in the case of the college student, and there were zero cases for children. The application type of studies on physical activities using a social cognitive theory can be largely classified as three types. The results of the measurement using a sectional investigation for SCT objects were 2 cases, the application of SCT for promoting physical activities was 1 case, and the demonstration of evaluation for the effect of SCT objects presented 8 highest cases. Although the social cognitive theory in the characteristics of the classification of object applications can be classified as 10 objects, there were no cases that used 10 all objects, partial applications of the object were measured in 8 studies, and two cases presented no detailed considerations on the object. Most of studies used a part of the object where the application of self-efficacy were measured by 8 highest cases. In addition, there were no measurements on the situation, observation learning, answer and response, and self-management. The elements of attitude, cognitive activity, self-efficacy, and handicaps among the SCT object were commonly used, and studies that the self-efficacy largely affects on the promotion of physical activities presented the main current.

• 한국멀티미디어학회논문지
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• 제25권5호
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• pp.703-720
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• 2022

Based on the love styles theory used in psychology, this paper classifies users(Passionate Love, Game-playing Love, Friendship Love, Practical Love, Possessive Love, Altruistic Love) and investigates satisfaction with the motivation for using TikTok love videos(Entertainment, Social Relationship, Love skills-learning, Self-verification, Problem-solving) according to the theory of use and satisfaction. First, 414 users were selected to conduct TikTok surveys to collect data. Then, through the analysis of the research results, among the six love types, game-playing type and possessive type have a positive (+) impact on entertainment motivation and love skill-learning motivation. Game-playing type also have a positive (+) impact on social relationship motivation and self-verification motivation. In addition, altruistic type and possessive type are also factors to strengthen the motivation of self-verification. The altruistic type, possessive type and practical type will improve the problem-solving motivation. Finally, through hierarchial multiple regression analysis, it is confirmed that game-playing love type, entertainment motivation, love skill-learning motivation and self-verification motivation can improve user satisfaction. The above results enrich the research of user classification as well as providing inspiration for improving the quality and communication efficiency of TikTok's video and enhancing user experience.

• 한국도서관정보학회지
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• 제21권
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• pp.195-229
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• 1994

This article investigates the normative principles suggested by Rangannathan as the guiding principles for his theories, consisting of basic laws, fundamental laws, canons, principles and postulates. His five basic laws and five laws of library science are re-interpreted from the view point of library classification. And three planes of idea plane, verbal plane and notational plane, one of the core ideas in his analytico-synthetic theory of library classification, are analyzed. This article also suggests the demonstration model for this three planes using the ideas from chemistry ad chemical equation. In the last part, it analyzes the canons for library classification of three planes. These normative principles are basically guiding principles for so-called analytico-synthetic or faceted classification. But they can be a n.0, pplied to most of modern classification. But they can be a n.0, pplied to most of modern classification schemes, especially to semi-enumerative schemes including DDC, KDC, etc. so that they can improve the schemes. From this regard, these principles can also be helpful to the KDC, on the verge of the revision of its fourth edition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.672-674
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• 2000

There are various ways in classification methodologies of data mining such as neural networks but the result should be explicit and understandable and the classification rules be short and clear. Rough set theory is a effective technique in extracting knowledge from incomplete and inconsistent information and makes an offer classification and approximation by various attributes with effect. This paper discusses granularity of knowledge for reasoning of uncertain concepts by using generalized rough set approximations based on hierarchical granulation structure and uses hierarchical classification methodology that is more effective technique for classification by applying core to upper level. The consistency rules with minimal attributes is discovered and applied to classifying real data.

• Journal of Information Science Theory and Practice
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• 제1권1호
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• pp.10-26
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• 2013

Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.