Towards Developing Fuzzy Neighborhood Based Clustering Algorithms for High Performance Distributed Memory Computing Environments

ATILGAN C., TEZEL B. T., Nasibov E.

3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo, Bosna-Hersek, 20 - 23 Eylül 2018, ss.367-371 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ubmk.2018.8566594
  • Basıldığı Şehir: Sarajevo
  • Basıldığı Ülke: Bosna-Hersek
  • Sayfa Sayıları: ss.367-371
  • Anahtar Kelimeler: Fuzzy neighborhood, fuzzy clustering, high performance computing, distributed memory
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Fuzzy neighborhood-based clustering algorithms overcome the parameter selection problem of classical neighborhood based clustering algorithms and offer fully unsupervised, i.e. parameter free clustering. On the other hand, due to the inherent fuzzy-calculation-overhead, they demand higher processing time and memory compared to classical clustering algorithms. In some recent studies, these fuzzy algorithms have been improved, especially in terms of speed, such that they became applicable to large data sets. Nonetheless, they need to he adapted to multi-computer systems in order to he used in today's big data applications. The aim of this study is developing fuzzy neighborhood-based clustering algorithms which are designed to run on high performance distributed memory computing environments and revealing their effectiveness by testing them in a real big-data application.