Mining Closed Weighed Frequent Patterns from a Sliding Window over Data Stream

Cui Cui Ge; Xiu Fen Fu

doi:10.4028/www.scientific.net/AMR.756-759.2606

Paper Titles

Generalized Hamming Weights of Cyclic Codes from Algebraic Function Fields
p.2588

Analysis and Design of the JCVM Runtime Environment
p.2593

Research on Organization Tacit Knowledge Transferring: An Evolutionary Game Theoretic Analysis
p.2597

Research on Multi-Attribute Decision Making with Normal Distribution Weight
p.2602

Mining Closed Weighed Frequent Patterns from a Sliding Window over Data Stream
p.2606

Aspect-Oriented Programming and Modeling Based on UML
p.2610

Convergence of the Preconditioned AOR Method for an H-Matrix
p.2615

The Improved Genetic Algorithms Apply on Parameter Estimation of Two Parameters Logistic Model on Item Response Theory
p.2620

A Research on Genetic Algorithms Based on Test Paper Composition of Item Response Theory
p.2625

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759Mining Closed Weighed Frequent Patterns from a...

Mining Closed Weighed Frequent Patterns from a Sliding Window over Data Stream

Abstract:

Weighted frequent pattern mining address to discover more important frequent pattern by considering different weights of every item, closed frequent pattern mining can significantly reduce the number of frequent itemset mining and keep sufficient result information. In this paper,we proposed an algorithm DS_CRWF to mine closed weighted frequent pattern over data stream,which is based on sliding window and take basic window as unit of updating,all the closed weighted frequent patterns can be mined through once scan.The experimental results show the feasibility of the algorithm.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

2606-2609

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.2606

Citation:

Cite this paper

Online since:

September 2013

Authors:

Cui Cui Ge, Xiu Fen Fu

Keywords:

Closed Weighted Frequent Pattern, Data Mining (DM), Data Stream, DS_CRWF, Sliding Window

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] JIE W, YU Z. DSWFP-Miner: Mining Closed Weighted Frequent Pattern over Data Streams: 2011 IEEE 8th International Conference on Fuzzy Systems and Knowledge Discovery, 2011[C], Shanghai, China, 26-28 July (2011).

DOI: 10.1109/fskd.2011.6019763

Google Scholar

[2] LEUNG C K S, KHAN Q L. A Tree Structure For The Mining of Frequent Sets From Data Streams[C]: Proceedings of the 6th International Conference on Data Mining. Hong Kong, China.

DOI: 10.1109/icdm.2006.62

Google Scholar

[3] JIANG N, GRUENWALD L. CFI-stream：Mining Closed Frequent Itemsets in Data Streams[C]: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge and Data Mining. Philadelphia, USAI ACM Press, (2006).

DOI: 10.1145/1150402.1150473

Google Scholar

[4] LI H F, Ho C C, LEE S Y. Incremental Updates of Closed Frequent Itemsets Over Continuous Data Streams [J]. Expert Systems with Applications, 2009, 36: 2451-2458.

DOI: 10.1016/j.eswa.2007.12.054

Google Scholar

[5] JIA WEI H, PEI J. Mining Frequent Patterns Without Candidate Generation[C]: Proceedings of ACM SIGMOD International Conference Management of Data, (2000).

DOI: 10.1145/342009.335372

Google Scholar

[6] UNIL Y. Mining Lossless Closed Frequent Patterns With Weight Constraints[C]: Journal Knowledge-Based Systems archive Volume 20 Issue 1, February, (2007).

DOI: 10.1016/j.knosys.2006.07.007

Google Scholar

[7] JIE W, YU Z. DCWFP-Miner: Mining Closed Weighted Frequent Patterns over Data Streams[C]: 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2012).

DOI: 10.1109/fskd.2012.6233873

Google Scholar