Title :
A Parallel Mining Algorithm for Closed Sequential Patterns
Author :
Zhu, Tian ; Bai, Sixue
Author_Institution :
Dept. of Comput. Sci. & Technol., Nanchang Univ., Nanchang
Abstract :
Mining closed sequential patterns is an important data mining task with broad applications, the large dataset acquires us to use the parallel technique to solve the problems in data mining. A new parallel algorithm named Par-ClosP is introduced in this paper. It partitions the task to each processor, reduces the communication among the processors, uses pseudo projection technique to minimize the use of time and space, and it introduces a new pruning method, thus improves the efficiency of the algorithm.
Keywords :
data mining; parallel algorithms; Par-ClosP; closed sequential patterns; data mining task; parallel mining algorithm; pruning method; pseudo projection technique; Application software; Computer science; Data mining; Databases; Itemsets; Iterative algorithms; Parallel algorithms; Partial response channels; Pattern analysis; Sequences; closed sequential pattern; data mining; parallel algorithm; pseudo projection;
Conference_Titel :
Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference on
Conference_Location :
Niagara Falls, Ont.
Print_ISBN :
978-0-7695-2847-2
DOI :
10.1109/AINAW.2007.40