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  1. جستجو ساده
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  3. DSCLU: A new data stream CLUstring algorithm for multi density environments
DSCLU: A new data stream CLUstring algorithm for multi density environments
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DSCLU: A new data stream CLUstring algorithm for multi density environments

Namadchian, A.

  1. DOI:10.1109/SNPD.2012.119
  2. Main Entry: Namadchian, A.
  3. Title:DSCLU: A new data stream CLUstring algorithm for multi density environments.
  4. Publisher:2012.
  5. Abstract:Recently, data stream has become popular in many contexts of data mining. Due to the high amount of incoming data, traditional clustering algorithms are not suitable for this family of problems. Many data stream clustering algorithms proposed in recent years considered the scalability of data, but most of them did not attend the following issues: (1) The quality of clustering can be dramatically low over the time. (2) Some of the algorithms cannot handle arbitrary shapes of data stream and consequently the results are limited to specific regions. (3) Most of the algorithms have not been evaluated in multi-density environments. Identifying appropriate clusters for data stream by handling the arbitrary shapes of clusters is the aim of this paper. The gist of the overall approach in this paper can be stated in two phases. In online phase, data manipulate with specific data structure called micro cluster. This phase is activated by incoming of data. The offline phase is manually activated by coming a request from user. The algorithm handles clusters by considering with micro clusters created by the online phase. The experimental evaluation showed that proposed algorithm has suitable quality and also returns appropriate results even in multi-density environments
  6. Notes:Sharif Repository
  7. Subject:Arbitrary shape.
  8. Subject:Data stream.
  9. Subject:Data stream clustering.
  10. Subject:Density-based Clustering.
  11. Subject:DSCLU.
  12. Subject:Experimental evaluation.
  13. Subject:Micro-clusters.
  14. Subject:multi density environment clustering.
  15. Subject:Offline.
  16. Subject:Quality of clustering.
  17. Subject:Traditional clustering.
  18. Subject:Artificial intelligence.
  19. Subject:Data communication systems.
  20. Subject:Data mining.
  21. Subject:Data structures.
  22. Subject:Quality control.
  23. Subject:Software engineering.
  24. Subject:Clustering algorithms.
  25. Added Entry:Esfandani, G.
  26. Added Entry:Sharif University of Technology.
  27. Added Entry:13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012; Kyoto; Japan; 8 August 2012 through 10 August 2012
  28. Added Entry: SNPD 2012
  29. Source: Proceedings - 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2012 ; 2012 , Pages 83-88 ; 9780769547619 (ISBN)
  30. Web Site:http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6299262

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