On Reducing Space Complexity of Fuzzy Neighborhood Based Clustering Algorithms

ATILGAN C., Nasibov E.

2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Türkiye, 5 - 08 Ekim 2017, ss.577-579 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ubmk.2017.8093467
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.577-579
  • Anahtar Kelimeler: lustering, Fuzzy neighborhood, Fuzzy joint points
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Using fuzzy neighborhood relations in density-based clustering, like in Fuzzy Joint Points (FJP) algorithm, yields more robust and autonomous algorithms. Even though the fuzzy neighborhood based clustering methods are proven to be fast enough, such that tens of thousands of data can be handled under a second, the space complexity is still a limiting factor. In this study, a transformed HP algorithm with low space complexity is proposed.