MISC

査読有り
2017年7月1日

ART-2b: Adapted ART-2a for large scale data clustering on PM2.5 mass spectra

Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
  • Nat Pavasant
  • ,
  • Hiroshi Furutani
  • ,
  • Masayuki Numao
  • ,
  • Ken Ichi Fukui

2018-January
開始ページ
4813
終了ページ
4815
DOI
10.1109/BigData.2017.8258551

© 2017 IEEE. ART-2a has been shown to be effective against stream data clustering with unknown number of cluster in nature. As data grows, ART-2a running time become a major problem. We proposed a new algorithm, ART-2b, whose runtime performance is linear to the number of input instances, while still maintaining similar clustering result to ART-2a.

リンク情報
DOI
https://doi.org/10.1109/BigData.2017.8258551
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