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Frequent pattern mining with uncertain data

Frequent pattern mining with uncertain data,10.1145/1557019.1557030,Charu C. Aggarwal,Yan Li,Jianyong Wang,Jing Wang

Frequent pattern mining with uncertain data   (Citations: 31)
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This paper studies the problem of frequent pattern mining with uncertain data. We will show how broad classes of algorithms can be extended to the uncertain data setting. In particular, we will study candidate generate-and-test al- gorithms, hyper-structure algorithms and pattern growth based algorithms. One of our insightful observations is that the experimental behavior of different classes of algorithms is very different in the uncertain case as compared to the deterministic case. In particular, the hyper-structure and the candidate generate-and-test algorithms perform much better than tree-based algorithms. This counter-intuitive behavior is an important observation from the perspective of algorithm design of the uncertain variation of the prob- lem. We will test the approach on a number of real and synthetic data sets, and show the effectiveness of two of our approaches over competitive techniques. Executable and Data Sets: Available at: http://dbgroup.cs.tsinghua.edu.cn/liyan/u mining.tar.gz
Conference: Knowledge Discovery and Data Mining - KDD , pp. 29-38, 2009
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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...

    • ...nature [1,2,26]. It only handles the uncertain edges and quantifies the uncertainty with the probability distributions...

    Yi Jiaet al. An efficient graph-mining method for complicated and noisy data with r...

    • ...These kinds of graphs are called uncertain graphs [1]...
    • ...And uncertainties because of noise in accuracy or dynamic nature of topological structure make it an uncertain graph [1]...
    • ...Thus according to [1], an exact graph is a special uncertain graph with existence possibilities of 1 on all edges...
    • ...Let minsup be the expected support threshold and ε Є [0, 1] be a relative error tolerance...
    • ...<{[SECTION]}>threshold minsup є [0, 1], a relative error tolerance ε є [0, 1] and...
    • ...<{[SECTION]}>threshold minsup є [0, 1], a relative error tolerance ε є [0, 1] and...
    • ...<{[SECTION]}>a real number δ є [0, 1]. Initially Weight factor of all edges is...

    Shawana Jamilet al. Weighted MUSE for Frequent Sub-Graph Pattern Finding in Uncertain DBLP...

    • ...In the data mining field, various mining techniques, such as clustering [9], [10], [11], [12], [13], [14] and frequent pattern mining techniques [15], [16], [17], are migrated from certain data to deal with uncertain data...

    Bin Jianget al. Outlier detection on uncertain data: Objects, instances, and inference...

    • ...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...

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