• Journal of Distribution Research
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• v.12 no.2
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• pp.103-129
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• 2007

One of the most enduring concepts in the history of marketing thought relates to the classification of consumer goods. The product classification theory first proposed by Copeland(1923) has, with little modification, survived to the present day, and continues to be endorsed by the American Marketing Association and other related institutions some 80 years after it was first published. In truth, Copeland's classification is now outdated and bears little, if any, relevance to modern product advertising, retailing and consumption. In particular, it can not accommodate the fact that, in modern societies, consumer preoccupations with style, personal identity and status have meant that the social characteristics of goods, heavily promoted by brand managers who understand their markets, are key determinants of consumer choice and buyer behavior. In this respect, the author attempted to explore the reasons why product classification theory has been unresponsive to changes in market conditions over so many years and argue that its failure to embrace the many social influences on consumption and on consumer behavior is now its most serious weakness. And also, the author proposed the new categorization system of goods, based on the several existing literatures.

• Journal of applied mathematics & informatics
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• v.3 no.2
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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.

• Management & Information Systems Review
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• v.1
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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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• v.36 no.3
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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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• v.2 no.1
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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.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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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.

• Journal of Korea Multimedia Society
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• v.25 no.5
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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.

• Journal of Korean Library and Information Science Society
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• v.21
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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.

• Proceedings of the KIEE Conference
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• 2000.11d
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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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• v.1 no.1
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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.