EclatDS: An efficient sliding window based frequent pattern mining method for data streams

2011 ◽  
Vol 15 (4) ◽  
pp. 571-587 ◽  
Author(s):  
Mahmood Deypir ◽  
Mohammad Hadi Sadreddini
2009 ◽  
Vol 179 (22) ◽  
pp. 3843-3865 ◽  
Author(s):  
Syed Khairuzzaman Tanbeer ◽  
Chowdhury Farhan Ahmed ◽  
Byeong-Soo Jeong ◽  
Young-Koo Lee

2009 ◽  
Vol E92-D (7) ◽  
pp. 1369-1381 ◽  
Author(s):  
Chowdhury Farhan AHMED ◽  
Syed Khairuzzaman TANBEER ◽  
Byeong-Soo JEONG ◽  
Young-Koo LEE

Author(s):  
Aleardo Junior Manacero ◽  
Renata Spolon Lobato ◽  
Marcos Antônio Cavenaghi ◽  
Alexandre Colombo ◽  
Roberta Spolon

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.


Sign in / Sign up

Export Citation Format

Share Document