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Research on Personal Learning System Based on Data Mining
Author: ShiChunXiu
Tutor: HeZuoLian
School: Tianjin University
Course: Applied Computer Technology
Keywords: Data Mining Network learning behavior Personalized Learning System Personalized Recommendation
CLC: TP391.6
Type: Master's thesis
Year: 2007
Downloads: 254
Quote: 1
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Abstract
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Present , with the launching of distance education , Web-based learning has made considerable progress ; However, there are some problems . For example , the network teaching widespread single teaching mode , teaching simple accumulation of resources , the low degree of intelligence , educated object learning ability , personal interests and habits , personal learning foundation , level of effort , there is a huge difference . The resulting network teaching platform can not meet the needs of learners personalized contradiction . Therefore, how to make the network learning system to support personalized service , is one of the urgent problems of the field of online education . Behavior for network learning and data mining technology features , analysis and research on personalized learning system , the main work is as follows: The network learning behavior and learner personalized analysis algorithm based - data mining and clustering analysis . Better path mining algorithms based FLaAT frequent Web user browse combined network learner browsing behavior , consider a different prefix the same sub- path merge search learners prefer browsing path analysis examples , making mining information . The given the learner preference path mining algorithms - learners fuzzy weighted preference navigation path mining algorithms MingLearner . The focus of the algorithm to consider teaching web weight , and this weight is given by the teacher or teaching experts semantic assessment method calculated using fuzzy math . Thus more in line with the learning rules to better reflect learners' interests and preferences . Combined the network learner behavior Affairs , proposed a clustering algorithm based on fuzzy similarity relation , and two examples of learner behavior clustering further analyzed . Build data mining application in the construction of a personalized learning system focuses on individualized learning in a personalized learning system recommended modules and data mining processing module . Concludes the paper and look forward to further work .
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Teaching machine, learning machine
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