NDLI: An efficient parallel FP-Growth algorithm

Content Provider	IEEE Xplore Digital Library
Author	Min Chen XueDong Gao HuiFei Li
Copyright Year	2009
Description	Author affiliation: School of Economics and Management, University of Science and Technology Beijing, Beijing, P.R. China (Min Chen; XueDong Gao) \|\| Soft Ware Group, IBM Global Services (China) Company Limited, Beijing, P.R. China (HuiFei Li)
Abstract	FP-Growth algorithm recursively generates huge amounts of conditional pattern bases and conditional FP-trees when the dataset is huge. In such a case, both the memory usage and computational cost are expensive, such that, the FP-tree can not meet the memory requirement. In this work, we propose a novel parallel FP-Growth algorithm, which is designed to run on the computer cluster. To avoid memory overflow, this algorithm finds all the conditional pattern bases of frequent items by the projection method without constructing an FP-tree. Hereafter, it splits the mining task into number of independent sub-tasks, executes these sub-tasks in parallel on nodes and then aggregates the results back for the final result. Our algorithm works independently at each node. As a result, it can efficiently reduce the inter-node communication cost. Experiments show that this parallel algorithm not only avoids the memory overflow but accelerate the computational speed. In addition, it achieves much better scalability than that of the FP-Growth algorithm.
Starting Page	283
Ending Page	286
File Size	110130
Page Count	4
File Format	PDF
ISBN	9781424452187
DOI	10.1109/CYBERC.2009.5342148
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Parallel algorithm Computer cluster FP-Growth Data structures Data mining Parallel algorithms Concurrent computing Databases Aggregates Clustering algorithms Computational efficiency Acceleration
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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