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    1
    A Hybrid Predictive Maximal Frequent Itemset Mining Algorithm On P2P Network
    • Department of Computer Science and Information Engineering /100/ Master
    • Author: Hsin-Hsien Lu   Advisor: Chyouhwa Chen 、 Wei-Chung Teng
    • Abstract—We propose a novel algorithm for distributed maximal frequent itemset mining in unstructur…
    • Clicks: 646  Downloads: 0 
    • Full text public date 2017/07/31 (Intranet public)
    • Full text public date This full text is not authorized to be published. (Internet public)
    • Full text public date This full text is not authorized to be published. (National library)

    2
    Predictive Search Approach to Maximal Frequent Itemset Mining on P2P Networks
    • Department of Computer Science and Information Engineering /98/ Master
    • Author: SHEA-YU YELLOW   Advisor: Chyou-Hwa Chen
    • Predictive Search Approach to Maximal Frequent Itemset Mining on P2P Networks
    • Clicks: 623  Downloads: 0 
    • Full text public date 2015/08/02 (Intranet public)
    • Full text public date This full text is not authorized to be published. (Internet public)
    • Full text public date This full text is not authorized to be published. (National library)

    3
    A Predictive Maximal Frequent Itemset Mining Algorithm On P2P Network
    • Department of Computer Science and Information Engineering /100/ Master
    • Author: Tung-chen Lin   Advisor: Chyou-Hwa Chen
    • Association rule mining is one of most popular problems in the field of data mining. We propose a n…
    • Clicks: 454  Downloads: 0 
    • Full text public date 2017/08/06 (Intranet public)
    • Full text public date This full text is not authorized to be published. (Internet public)
    • Full text public date This full text is not authorized to be published. (National library)

    4
    Efficient Mining of Maximal Frequent Itemsets Based on Maximal Clique Trees
    • Department of Electronic and Computer Engineering /112/ Master
    • Author: Shu-Yu Chen   Advisor: Wei-Mei Chen
    • Frequent itemset mining is one of the important domains in data mining. It aims to find out the ass…
    • Clicks: 311  Downloads: 0 
    • Full text public date 2034/01/15 (Intranet public)
    • Full text public date This full text is not authorized to be published. (Internet public)
    • Full text public date This full text is not authorized to be published. (National library)
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