A half-split grid clustering algorithm by simulating cell division

Wenxiang Dou, Jinglu Hu

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

Clustering, one of the important data mining techniques, has two main processing methods on data-based similarity clustering and space-based density grid clustering. The latter has more advantage than the former on larger and multiple shape and density dataset. However, due to a global partition of existing grid-based methods, they will perform worse when there is a big difference on the density of clusters. In this paper, we propose a novel algorithm that can produces appropriate grid space in different density regions by simulating cell division process. The time complexity of the algorithm is O(n) in which n is number of points in dataset. The proposed algorithm will be applied on popular chameleon datasets and our synthetic datasets with big density difference. The results show our algorithm is effective on any multi-density situation and has scalability on space optimization problems.

本文言語English
ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2183-2189
ページ数7
ISBN(電子版)9781479914845
DOI
出版ステータスPublished - 2014 9 3
イベント2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
継続期間: 2014 7 62014 7 11

出版物シリーズ

名前Proceedings of the International Joint Conference on Neural Networks

Conference

Conference2014 International Joint Conference on Neural Networks, IJCNN 2014
CountryChina
CityBeijing
Period14/7/614/7/11

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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