'1+1>2': Merging distance and density based clustering

M. Dash, Huan Liu, Xiaowei Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Scopus citations

Abstract

Clustering is an important data exploration task. Its use in data mining is growing very fast. Traditional clustering algorithms which no longer cater for the data mining requirements are modified increasingly. Clustering algorithms are numerous which can be divided in several categories. Two prominent categories are distance-based and density-based (e.g. K-means and DBSCAN, respectively). While K-means is fast, easy to implement and converges to local optima almost surely, it is also easily affected by noise. On the other hand, while density-based clustering can find arbitrary shape clusters and handle noise well, it is also slow in comparison due to neighborhood search for each data point, and faces a difficulty in setting the density threshold properly. We propose BRIDGE that efficiently merges the two by exploiting the advantages of one to counter the limitations of the other and vice versa. BRIDGE enables DBSCAN to handle very large data efficiently and improves the quality of K-means clusters by removing the noisy points. It also helps the user in setting the density threshold parameter properly. We further show that other clustering algorithms can be merged using a similar strategy. An example given in the paper merges BIRCH clustering with DBSCAN.

Original languageEnglish (US)
Title of host publicationProceedings - 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-39
Number of pages8
ISBN (Print)0769509967, 9780769509969
DOIs
StatePublished - 2001
Event7th International Conference on Database Systems for Advanced Applications, DASFAA 2001 - Hong Kong, China
Duration: Apr 18 2001Apr 21 2001

Other

Other7th International Conference on Database Systems for Advanced Applications, DASFAA 2001
CountryChina
CityHong Kong
Period4/18/014/21/01

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Dash, M., Liu, H., & Xu, X. (2001). '1+1>2': Merging distance and density based clustering. In Proceedings - 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001 (pp. 32-39). [916361] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DASFAA.2001.916361