Title :
A Improved PrefixSpan algorithm for sequential pattern mining
Author :
Liang Dong ; Wang Hong
Author_Institution :
Inst. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
Abstract :
Aiming at the problem of constructing huge amounts of projected databases in PrefixSpan algorithm, this paper proposes an Improved PrefixSpan algorithm for Mining Sequential Patterns, called BLSPM algorithm (based on bi-level Sequential Patterns Mining). The algorithm use duplicated projection and certain specific sequential patterns pruning, reduce the scale of projected databases and the runtime of scanning projected databases, thus, the efficiency of algorithm could be raised up greatly, and all needed sequential patterns are obtained. Experiment results shows that BLSPM algorithm is more efficient than PrefixSpan algorithm in large databases.
Keywords :
data mining; database management systems; BLSPM algorithm; PrefixSpan algorithm; bi-level sequential patterns mining; duplicated projection; projected databases; sequential patterns pruning; Algorithm design and analysis; Data mining; Databases; Heuristic algorithms; Iron; Runtime; Software algorithms; PrefixSpan algorithm; prejected database; sequential pattern;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933586