• Title/Summary/Keyword: Classification Strategy

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A Microgenetic Analysis on the Classification Strategy Used in Tasks Related to Science by College Students (대학생이 과학 관련 과제에서 사용한 분류 전략의 미시발생적 분석)

  • Choi, Hyun-Dong
    • Journal of the Korean Society of Earth Science Education
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    • v.4 no.2
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    • pp.151-165
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    • 2011
  • Following a microgenetic design, this study was analysed the characteristic and the change of classification strategy that appear in college students' classification activity. The 4 tasks were developed for classification activity; a shell as a familiar real things, an animal fossil as a unfamiliar real things, a snow flake as a familiar picture cards and galaxy as a unfamiliar picture card. Achieved study to 6 college students who major in elementary education. Data were collected by interview with subjects, subject's classification schema, investigator's observation of subject's activity, and videotaped that record subject's subject classification process over an extended period of 6 times. Result proved in this study is as following. In the 6 times of the data collection procedures, a strategy F identifying concrete attribution of classification objects and a more detailed strategy X3 combining qualitative, spatial and dimensional attribution were found and more frequently used in both groups of college students which reported a classification process and did not report the process. While discovery and absorption of both a concrete classification strategy and a detailed classification strategy were rapidly developed in the reporting group, they were gradually developed in the non-reporting group. In addition to this, as the data collection procedures were progressing, the college students were familiar with change factors of classification tasks and in the case of pictures the classification strategy showed more desirable changes.

Type of Classification Criterion and Characteristic of Classification Strategy That Appear in Pre-Service Elementary Teachers' Classification Activity (예비 초등 교사들의 분류 활동에서 나타난 분류 기준의 유형과 분류 전략의 특징)

  • Yang, Il-Ho;Choi, Hyun-Dong
    • Journal of Korean Elementary Science Education
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    • v.27 no.1
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    • pp.9-22
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    • 2008
  • The purpose of this study was to investigate the type of classification criterion and the characteristic of classification strategy that appear in pre-service elementary teachers' classification activity. The 4 tasks were developed for classification activity; button as a real things that attribute is prominent, shell as a real things that attribute is less prominent, snow flake as a picture cards that attribute is prominent, and galaxy as a picture cards that attribute is less prominent. The 5 college students who major in elementary education were selected. Data were collected by interview with participants, participants' classification recording paper, investigator's observation of participants' action observation, and videotaped that record participants' subject classification process. Result proved in this study is as following. First, pre-service elementary teachers used 4 qualitative classification criterion of feature, random field, image and secondary property, and used 2 dimension classification criterion of space and quantity. They used single quality classification criterion or combining dimension classification criterion in classification activity. Second, pre-service elementary teachers have classification strategy that apply each various classification criterion, and also classification strategy are different according to subject, but discussed that "anchor" and "priming effect" are important for effective classification. Result of this study is expected to contribute classification research and classification teaching program development.

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Product Classifications Revisited with Transparency Effect: A Forgotten Link Between Consumer Research and Marketing Strategy

  • Suh, Jaebeom;Deeter-Schmelz, Dawn;Suh, Taehyun;Jin, Hyun Seung
    • Asia Marketing Journal
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    • v.20 no.1
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    • pp.49-68
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    • 2018
  • It is appropriate and useful to interpret some product classification schemes as buyer behavior models; such classifications permit investigations of discrepancies between classification predictions and actual buyer behavior. We review existing product classifications and identify underlying behavioral assumptions of various classification schemes that have been used in the marketing discipline for more than nine decades. Recognizing the irrelevance of existing product classifications for current products, we propose a new reclassification framework by incorporating transparency concepts. Based on this extended product classification, we highlight the potential roles of product classification study as an important link between consumer research and marketing strategy, emphasizing behavioral implications.

Note on classification and regression tree analysis (분류와 회귀나무분석에 관한 소고)

  • 임용빈;오만숙
    • Journal of Korean Society for Quality Management
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    • v.30 no.1
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    • pp.152-161
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    • 2002
  • The analysis of large data sets with hundreds of thousands observations and thousands of independent variables is a formidable computational task. A less parametric method, capable of identifying important independent variables and their interactions, is a tree structured approach to regression and classification. It gives a graphical and often illuminating way of looking at data in classification and regression problems. In this paper, we have reviewed and summarized tile methodology used to construct a tree, multiple trees and the sequential strategy for identifying active compounds in large chemical databases.

Applying Strategy Group Concept to Program Providers(PP) Industry (PP 산업에 대한 전략집단 개념의 적용)

  • Yeo, Hyun-Chul;Kim, Young-Soo
    • The Journal of the Korea Contents Association
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    • v.11 no.1
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    • pp.357-370
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    • 2011
  • Using strategy group theory, this thesis reviewed the status of program providers analysis and the performances it has made so far, and sought measures to improve its limitations. The constraint of program providers analysis based on existing concept of strategy group is that the strategy group was derived from the statistics, and therefore only applied the characteristics of program provider's channels to the analysis, on account of which a systematic and sophisticated classification as well as generalization of strategy or strategy group were hard to obtain. Moreover, the PP strategy variables used to be selected at the firm level and business level, and in relation with resource and competition scope. In future, more appropriate procedure should be followed to obtain objectivity in selecting variables to avoid controversy over intentionality. The measures in this thesis to improve the study of PP strategy group can be summarized as follows: firstly analysis of variables for strategy group classification should be made to single out key variables which are to be classification criteria. Secondly, variables are to be cross-checked by industry experts to increase generalizability. Thirdly, proxy variables should be sublated, and strategy group model which enables the reflection of subsistent properties of PP industry, and the cognitive perception of the executives(CEO) needs to be established. Fourthly, the concepts of mobility barrier and isolating mechanism should be applied to the classification criteria of strategy group to reveal the gap of performance between different strategy groups. Lastly, chronicle study on PP strategy group should be done to perceive the dynamic changes of PP strategy group.

Functional Classification of Myoelectric Signals Using Neural Network for a Artificial Arm Control Strategy (인공팔 제어를 위한 근전신호의 신경회로망을 이용한 기능분석)

  • 손재현;홍성우;남문현
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.43 no.6
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    • pp.1027-1035
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    • 1994
  • This paper aims to make an artificial arm control strategy. For this, we propose a new feature extraction method and design artificial neural network for the functional classification of myoelectric signal(MES). We first transform the two channel myoelectric signals (MES) for biceps and triceps into frequency domain using fast Fourier transform (FFT). And features were obtained by comparing the magnitudes of ensemble spectrum data and used as inputs to the three-layer neural network for the learning. By changing the number of units in hidden layer of neural network we observed the improvement of classification performance. To observe the effeciency of the proposed scheme we performed experiments for classification of six arm functions to the three subjects. And we obtained on average 94[%] the ratio of classification.

Import Vector Voting Model for Multi-pattern Classification (다중 패턴 분류를 위한 Import Vector Voting 모델)

  • Choi, Jun-Hyeog;Kim, Dae-Su;Rim, Kee-Wook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.655-660
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    • 2003
  • In general, Support Vector Machine has a good performance in binary classification, but it has the limitation on multi-pattern classification. So, we proposed an Import Vector Voting model for two or more labels classification. This model applied kernel bagging strategy to Import Vector Machine by Zhu. The proposed model used a voting strategy which averaged optimal kernel function from many kernel functions. In experiments, not only binary but multi-pattern classification problems, our proposed Import Vector Voting model showed good performance for given machine learning data.

Development of Learning Strategy Scale for College Students (전문대학생을 위한 학습전략 진단 도구의 개발)

  • PARK, Sung-Mi
    • Journal of Fisheries and Marine Sciences Education
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    • v.21 no.1
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    • pp.16-27
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    • 2009
  • The purpose of this study was to develop of learning strategy scale for college students. This study further classified several sub-areas and defined each concepts of learning strategy. Based upon the classification of each sub-areas, tentative test items were developed through the verification of validity by three professionals. A pilot study of the developed scale was administered to 239 college students. And the research collected major data from 1,012 college students. Data were analyzed to obtain item quality, reliability, and validity analysis. The results of this study were as follows. The scale for learning strategy was defined by eight factors and they were 'self-management strategy', 'examination-readiness strategy', 'cognitive strategy', 'memorizing strategy', 'reporting strategy', 'resource-utilization strategy', 'self-regulated strategy', 'cooperative learning strategy'. The results of the confirmatory factor analysis proved the eight factors in the learning strategy. And criterion validity evidence was also obtained from a correlation analysis of the level of academic achievement.

Defense Strategy of Network Security based on Dynamic Classification

  • Wei, Jinxia;Zhang, Ru;Liu, Jianyi;Niu, Xinxin;Yang, Yixian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.12
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    • pp.5116-5134
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    • 2015
  • In this paper, due to the network security defense is mainly static defense, a dynamic classification network security defense strategy model is proposed by analyzing the security situation of complex computer network. According to the network security impact parameters, eight security elements and classification standard are obtained. At the same time, the dynamic classification algorithm based on fuzzy theory is also presented. The experimental analysis results show that the proposed model and algorithm are feasible and effective. The model is a good way to solve a safety problem that the static defense cannot cope with tactics and lack of dynamic change.