Deep learning frequent pattern mining on static semi structured data streams for improving fast speed and complex data streams

Author(s):  
G. Suseendran ◽  
D. Balaganesh ◽  
D. Akila ◽  
Souvik Pal
2009 ◽  
Vol 179 (22) ◽  
pp. 3843-3865 ◽  
Author(s):  
Syed Khairuzzaman Tanbeer ◽  
Chowdhury Farhan Ahmed ◽  
Byeong-Soo Jeong ◽  
Young-Koo Lee

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.


2014 ◽  
Vol 37 ◽  
pp. 109-116 ◽  
Author(s):  
Shamila Nasreen ◽  
Muhammad Awais Azam ◽  
Khurram Shehzad ◽  
Usman Naeem ◽  
Mustansar Ali Ghazanfar

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