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Research on Mining Personalized Information in Online Interaction and Learning Platform

Author: WeiQinQin
Tutor: DingZhenGuo
School: Xi'an University of Electronic Science and Technology
Course: Educational Technology
Keywords: network education data mining FP-growth personalized
CLC: TP311.13
Type: Master's thesis
Year: 2009
Downloads: 45
Quote: 0
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Abstract


The paper introduces the association rules technique in data mining and applies it to the analysis and research on mining personalized information in online interaction and learning platform.It firstly discuses the application of data mining in the education filed, studies the basic theories and algorithms of data mining; Then the key techniques of design and implementation are studied in the module of mining personalized information:data preprocessing, mining frequent itemsets, rules extraction and result processing. In mining frequent itemsets, FP-growth algorithm with better performance is chosen, with regard to the problem in its efficiency, an improved algorithm is proposed; In extracting rules, a frame combined by support, confidence and correlation is used after considering the false rule caused by negative interrelation; Finally, an instance is used to verify the feasibility and utility of the designed personalized information mining module according to the above research results.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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