Survey: Running and comparing stream clustering algorithms

Ahmed R. D., Dalkılıç G., Erten M.

12th Turkish National Software Engineering Symposium, UYMS 2018, İstanbul, Türkiye, 10 - 12 Eylül 2018, cilt.2201 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 2201
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Clustering, Data Mining, Data Stream Clustering, Density-base Algorithms
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Recently, clustering data streams have become an incredibly important research area for knowledge discovery as applications produce more and more unstoppable streaming data. In this paper we introduce clustering, streams and data streaming clustering algorithms, as well as discussions of the most important stream clustering algorithms, considering their structure. As an additional contribution of our work and differently from review and survey papers in stream clustering, we offer the practical part of the most known stream clustering algorithms, namely: (i) CluStream; (ii) DenStream; (iii) D-Stream; and (iv) ClusTree, showing their experimental results along with some performance metrics computation of for each, depending on MOA framework.