Title :
A Frequent Itemsets Mining Algorithm Based on Matrix in Sliding Window over Data Streams
Author :
Fan Guidan ; Yin Shaohong
Author_Institution :
Sch. of Comput. Sci. & Software Eng., Tianjin Polytech. Univ., Tianjin, China
Abstract :
According to the nature of data stream which can only scans database several times, this paper proposed a mining frequent item sets algorithm based on matrix in sliding window over data streams. The algorithm used two 0-1 matrices to store transaction and 2-itemsets, then we could get frequent item sets through some relative operation of the two matrices. Experimental results demonstrated the efficiency of the algorithm.
Keywords :
data mining; matrix algebra; 0-1 matrices; data streams; frequent itemsets mining algorithm; sliding window; Algorithm design and analysis; Approximation algorithms; Data mining; Educational institutions; Itemsets; Real-time systems; Software algorithms; data stream; frequent itemsets; matrix; sliding window;
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
DOI :
10.1109/ISDEA.2012.23
