Journal of Guangdong University of Technology ›› 2014, Vol. 31 ›› Issue (3): 39-43.doi: 10.3969/j.issn.1007-7162.2014.03.007

• Comprehensive Studies • Previous Articles     Next Articles

A Recognition Algorithm of Noise Applied to Environments with Intensive Noise-data Distribution

Chen Pinghua，Zhou Peng   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006,China
  • Received:2014-04-04 Online:2014-09-30 Published:2014-09-30

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Abstract: By combining the PageRank algorithm with the features of intensive noisedata to improve the noise-data recognition rate of DBSCAN in environments with intensive Noise-Point distribution, it structured the inner-cluster mapping function for voting, and proposed the inter-cluster voting noise recognition algorithmNoiseRank. Experimental results show that in environments with intensive NoisePoint distribution, the Noise-data recognition rate of NoiseRank is much higher than that of DBSCAN.

Key words: noise-data recognition, environments with intensive noise-point distribution, inner-cluster voting, DBSCAN, PageRank

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