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Mining Frequent Itemsets from Uncertain Data

Mining Frequent Itemsets from Uncertain Data,10.1007/978-3-540-71701-0_8,Chun-Kit Chui,Ben Kao,Edward Hung

Mining Frequent Itemsets from Uncertain Data   (Citations: 44)
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We study the problem of mining frequent itemsets from un- certain data under a probabilistic framework. We consider transactions whose items are associated with existential probabilities and give a for- mal definition of frequent patterns under such an uncertain data model. We show that traditional algorithms for mining frequent itemsets are either inapplicable or computationally inefficient under such a model. A data trimming framework is proposed to improve mining efficiency. Through extensive experiments, we show that the data trimming tech- nique can achieve significant savings in both CPU cost and I/O cost.
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    • ...2009; Gao and Wang 2010; Qin, Xia, and Li 2010), frequent item mining (Chui, Kao, and Hung 2007; Chui and Kao 2008; Zhang, Li, and Yi 2008a; Aggarwal, Li, and Wang 2009; Bernecker, Kriegel, Renz, Verhein, and Zuefle 2009), graph mining (Zou, Li, Gao, and Zhang 2010a,c; Zou, Gao, and Li 2010b; Chen and Wang 2010), outlier detection (Yu 2008), etc...

    Jiazhen Heet al. Learning naive Bayes classifiers from positive and unlabelled examples...

    • ...2009; Gao and Wang 2010; Qin, Xia, and Li 2010), frequent item mining (Chui, Kao, and Hung 2007; Chui and Kao 2008; Zhang, Li, and Yi 2008a; Aggarwal, Li, and Wang 2009; Bernecker, Kriegel, Renz, Verhein, and Zuefle 2009), graph mining (Zou, Li, Gao, and Zhang 2010a,c; Zou, Gao, and Li 2010b; Chen and Wang 2010), outlier detection (Yu 2008), etc...

    Jiazhen Heet al. Learning naive Bayes classifiers from positive and unlabelled examples...

    • ...Some researches have extended association rules mining techniques to imprecise or uncertain data [12,15,22,48,49]...
    • ...Chui et al. [15] discover frequent itemsets from uncertain data under a probabilistic framework which associate items of transactions with existential probabilities...

    Cheng-Hsiung Wenget al. Mining fuzzy association rules from uncertain data

    • ...Apart from studies in partition-based uncertain data clustering, other directions in uncertain data mining include density-basedclustering(e.g.,FDBSCAN[15]),frequentitem set mining [20], and density-based classification [21]...

    Ben Kaoet al. Clustering Uncertain Data Using Voronoi Diagrams and R-Tree Index

    • ...After all, computing the support of an itemset now has to rely on the existence probabilities of the items, which leads to an expected support as introduced by Chui et al. [4]...
    • ...Under the assumption of statistical independence of the items in all transactions in the dataset, the support of an itemset in this model, as defined by Chui et al. [4], is based on the possible world interpretation of uncertain data...
    • ...U-Apriori [4] is based on a level wise algorithm and represents a baseline algorithm for mining frequent itemsets from uncertain datasets...

    Toon Calderset al. Efficient Pattern Mining of Uncertain Data with Sampling

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