SpaRClus: Spatial relationship pattern-based hierarchical clustering

Sangkyum Kim, Xin Jin, Jiawei Han

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

Abstract

For the past decade, the need of multimedia mining has increased tremendously, especially in image data due to inexpensive digital technologies and fast mounting of image data. In this paper, we, first, show an algorithm, SpIBag (Spatial Item Bag Mining), which discovers frequent spatial patterns in images. Due to the properties of image data, SpIBag considers a bag of items together with a spatial information as a pattern which persists over geometrical transformations, such as scaling, translation, and rotation. Then, based on SpIBag, we propose SpaRClus (Spatial Relationship Pattern-Based Hierarchical Clustering) to cluster image data. Our performance study shows that the method is effective and efficient.

Original languageEnglish (US)
Title of host publicationSociety for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130
PublisherSociety for Industrial and Applied Mathematics Publications
Pages49-60
Number of pages12
ISBN (Print)9781605603179
DOIs
StatePublished - 2008
Event8th SIAM International Conference on Data Mining 2008, Applied Mathematics 130 - Atlanta, GA, United States
Duration: Apr 24 2008Apr 26 2008

Publication series

NameSociety for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130
Volume1

Other

Other8th SIAM International Conference on Data Mining 2008, Applied Mathematics 130
Country/TerritoryUnited States
CityAtlanta, GA
Period4/24/084/26/08

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Signal Processing
  • Theoretical Computer Science

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