Novel Approach for Frequent Pattern Algorithm for Maximizing Frequent Patterns in Effective Time

The essential aspect of mining association rules is to mine the frequent patterns. Due to native difficulty it is impossible to mine complete frequent patterns from a dense database. FP-growth algorithm has been implemented using an Array-based structure, known as the FP-tree,which is for storing compressed frequency information. Numerous experimental results have demonstrated that the algorithm performs extremely well. But in FP-growth algorithm, two traversals of FP-tree are needed for constructing the new conditional FP-tree. In this paper we present a novel Array Based Without Scanning Frequent Pattern (ABWSFP) tree technique that greatly reduces the need to traverse FP-trees, thus obtaining significantly improved performance for FP-tree based algorithms. The technique works especially well for large datasets. We then present a new algorithm which use the QFP-tree data structure in combination with the FP Tree- Experimental results show that the new algorithm outperform other algorithm in not only the speed of algorithms, but also their CPU consumption and their scalability.

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A Scalable Algorithm for Constructing Frequent Pattern Tree

International Journal of Intelligent Information Technologies ◽

10.4018/ijiit.2014010103 ◽

2014 ◽

Vol 10 (1) ◽

pp. 42-56 ◽

Cited By ~ 3

Author(s):

Zailani Abdullah ◽

Tutut Herawan ◽

A. Noraziah ◽

Mustafa Mat Deris

Keyword(s):

Data Structure ◽

Frequent Pattern ◽

Frequent Patterns ◽

Scalable Algorithm ◽

Tree Construction ◽

Frequent Pattern Tree ◽

Support Threshold ◽

Benchmark Datasets ◽

Tree Data ◽

Tree Data Structure

Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

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MERGEABLE DOUBLE-ENDED PRIORITY QUEUES

International Journal of Foundations of Computer Science ◽

10.1142/s0129054199000022 ◽

1999 ◽

Vol 10 (01) ◽

pp. 1-17 ◽

Cited By ~ 6

Author(s):

SEONGHUN CHO ◽

SARTAJ SAHNI

Keyword(s):

Data Structure ◽

Data Structures ◽

Priority Queue ◽

Priority Queues ◽

Experimental Results ◽

Tree Data ◽

Tree Data Structure

We show that the leftist tree data structure may be adapted to obtain data structures that permit the double-ended priority queue operations Insert, DeleteMin, DeleteMax, and Merge to be done in O( log n) time where n is the size of the resulting queue. The operations FindMin and FindMax can be done in O(1) time. Experimental results are also presented.

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A B-Tree Based Interval Consistency Control Method in DVE Systems

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.44-47.3269 ◽

2010 ◽

Vol 44-47 ◽

pp. 3269-3273

Author(s):

Wei Zhang ◽

Hang Jun Zhou ◽

Yu Xing Peng ◽

Si Kun Li

Keyword(s):

Data Structure ◽

Control Method ◽

Experimental Results ◽

Consistency Control ◽

Key Issues ◽

Tree Data ◽

Consistency Problem ◽

And Performance ◽

Tree Data Structure ◽

Determine System

The consistency problem is one of the key issues to determine system functionality and performance in DVE systems. The existing methods often cannot satisfy the requirements of order consistency and interval consistency at the same time, or impose a constraint relationship on receiver nodes which brings difficulties to optimize responsiveness. In this paper, we propose a novel interval consistency control method based on B-Tree data structure. The method can improve the overall responsiveness without compromising consistency functionality. Experimental results prove that our method can effectively improve the functionality and performance of DVE systems.

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