Research of a De-Noising Algorithm Based on Sliding Window

Wen Chuan Yang; Ying Hua Song; Ting Xi Gou

doi:10.4028/www.scientific.net/AMR.461.355

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 461Research of a De-Noising Algorithm Based on...

Research of a De-Noising Algorithm Based on Sliding Window

Abstract:

Top-quality and efficient service increases in importance in the telecom service. One of its challenging issues is to deal with the atypical incidents. While the traditional mining algorithms are focus on the high-frequent item sets, a de-noising algorithm related to the atypical incidents still remains unsettled. This paper proposed a de-noising model based on the sliding window. In this model, FP-tree and multi-association rules are introduced to fix the thresholds of the sliding window. Experimental results demonstrate that the proposed algorithm can apply an appropriate data set to the knowledge discovery of the atypical incidents

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Periodical:

Advanced Materials Research (Volume 461)

Pages:

355-359

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.461.355

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Online since:

February 2012

Authors:

Wen Chuan Yang, Ying Hua Song, Ting Xi Gou

Keywords:

Atypical Incident, Data Mining (DM), FP-Tree, Multi-Association Rules, Sliding Windows

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