Paper Title:
Maximal Frequent Item Sequences Mining
  Abstract

This work proposes a new fast algorithm finding maximal frequent item sequences from transaction database. Itemset is defined as item sequence (IS) for mining. Two lists called ISL (Item Sequence List) and FISL (Frequent Item Sequence List) are created by scanning database once for dividing n-IS into two categories depending on whether the IS to achieve minimum support number (n is the number of attributes). Sub item sequences (SIS) whose n-superset is in ISL are generated by recursion to make sure that each k-SIS appeared before its (k+1)-superset. As current k-SIS being joined to FISL, its (k-1)-SIS are pruned (k range from 2 to n-1). At last, all SISs whose n-superset is in FISL are pruned from FISL. We compare our new algorithm and FP-Growth by experiment to prove its superiority.

  Info
Periodical
Advanced Materials Research (Volumes 108-111)
Edited by
Yanwen Wu
Pages
1211-1216
DOI
10.4028/www.scientific.net/AMR.108-111.1211
Citation
L. J. Zhou, Z. Zhang, "Maximal Frequent Item Sequences Mining", Advanced Materials Research, Vols. 108-111, pp. 1211-1216, 2010
Online since
May 2010
Export
Price
$32.00
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