An overview of clustering methods in geographic data analysis

Jiawei Han, Jae Gil Lee, Micheline Kamber

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Clustering is the process of grouping a set of physical or abstract objects into classes of similar objects. A cluster is a collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters. Although classication is an effective means for distinguishing groups or classes of objects, it often requires costly collection and labeling of a large set of training tuples or patterns, which the classier uses to model each group. In contrast, clustering does not require such labeling at all.

Original languageEnglish (US)
Title of host publicationGeographic Data Mining and Knowledge Discovery, Second Edition
PublisherCRC Press
Pages149-188
Number of pages40
ISBN (Electronic)9781420073980
ISBN (Print)9781420073973
DOIs
StatePublished - Jan 1 2009

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ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)
  • Earth and Planetary Sciences(all)

Cite this

Han, J., Lee, J. G., & Kamber, M. (2009). An overview of clustering methods in geographic data analysis. In Geographic Data Mining and Knowledge Discovery, Second Edition (pp. 149-188). CRC Press. https://doi.org/10.1201/9781420073980