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Computer Science > Databases

arXiv:0904.3312 (cs)
[Submitted on 21 Apr 2009]

Title:HybridMiner: Mining Maximal Frequent Itemsets Using Hybrid Database Representation Approach

Authors:Shariq Bashir, Abdul Rauf Baig
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Abstract: In this paper we present a novel hybrid (arraybased layout and vertical bitmap layout) database representation approach for mining complete Maximal Frequent Itemset (MFI) on sparse and large datasets. Our work is novel in terms of scalability, item search order and two horizontal and vertical projection techniques. We also present a maximal algorithm using this hybrid database representation approach. Different experimental results on real and sparse benchmark datasets show that our approach is better than previous state of art maximal algorithms.
Comments: 8 Pages In the proceedings of 9th IEEE-INMIC 2005, Karachi, Pakistan, 2005
Subjects: Databases (cs.DB); Artificial Intelligence (cs.AI); Data Structures and Algorithms (cs.DS)
Cite as: arXiv:0904.3312 [cs.DB]
  (or arXiv:0904.3312v1 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.0904.3312
Related DOI: https://doi.org/10.1109/INMIC.2005.334484

Submission history

From: Shariq Bashir Mr. [view email]
[v1] Tue, 21 Apr 2009 18:38:25 UTC (137 KB)
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