A Rapid Incremental Frequent Pattern Mining Algorithm for Uncertain Data

Author(s):  
Tu-Liang Lin ◽  
Bo-Wei Wen ◽  
Hong-Yi Chang ◽  
Wan-Kun Chang ◽  
Shih-Che Hsu
2016 ◽  
Vol 20 (3) ◽  
pp. 571-594 ◽  
Author(s):  
Carson Kai-Sang Leung ◽  
Richard Kyle MacKinnon ◽  
Fan Jiang

2015 ◽  
Vol 42 (4) ◽  
pp. 2086-2097 ◽  
Author(s):  
Michela Antonelli ◽  
Pietro Ducange ◽  
Francesco Marcelloni ◽  
Armando Segatori

2012 ◽  
Vol 433-440 ◽  
pp. 4457-4462 ◽  
Author(s):  
Jun Shan Tan ◽  
Zhu Fang Kuang ◽  
Guo Gui Yang

The design of synopses structure is an important issue of frequent patterns mining over data stream. A data stream synopses structure FPD-Graph which is based on directed graph is proposed in this paper. The FPD-Graph contains list head node FPDG-Head and list node FPDG-Node. The operations of FPD-Graph consist of insert operation and deletion operation. A frequent pattern mining algorithm DGFPM based on sliding window over data stream is proposed in this paper. The IBM synthesizes data generation which output customers shopping a data are adopted as experiment data. The DGFPM algorithm not only has high precision for mining frequent patterns, but also has low processing time.


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