The framework of relative density-based clustering

Zelin Cui, Hong Shen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Density-based clustering, using two-phase scheme which consists of an online component and an offline component, is an effective framework for data stream clustering, it can find arbitrarily shaped clusters and capture the evolving characteristic of real-time data streams accurately. However, the clustering has some deficiencies on offline component. Most algorithm don’t adapt to the unevenly distributed data streams or the multi density distribution of the data streams. Moreover, they only consider the density and centroid to connect the adjacent grid and ignore similarity of attribute value between adjacent grids. In this paper, we calculate the similarity of neighboring grids and take the similarity as a weight that affects the connection of the neighboring grids and propose the relative density-based clustering that cluster the grids based on relative difference model that considers the density, centroid and the weight of similarity between adjacent grids, simply, we connect neighboring grids which are the relative small difference to form clusters on offline component. The experimental results have shown that our algorithm apply to the unevenly distributed data streams and has better clustering quality.

Original languageEnglish
Title of host publicationParallel Architecture, Algorithm and Programming - 8th International Symposium, PAAP 2017, Proceedings
EditorsHong Shen, Guoliang Chen, Mingrui Chen
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9789811064418
Publication statusPublished - 2017
Externally publishedYes
Event8th International Symposium on Parallel Architectures, Algorithms, and Programming, PAAP 2017 - Haikou, China
Duration: 17 Jun 201718 Jun 2017

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference8th International Symposium on Parallel Architectures, Algorithms, and Programming, PAAP 2017


  • Density-based clustering
  • Relative density-based clustering
  • Similarity of the neighboring grids


Dive into the research topics of 'The framework of relative density-based clustering'. Together they form a unique fingerprint.

Cite this