High Performance Clustering Based on the Similarity Join

  title={High Performance Clustering Based on the Similarity Join},
  author={Christian B{\"o}hm and Bernhard Braunm{\"u}ller and Markus M. Breunig and Hans-Peter Kriegel},
A broad class of algorithms for knowledge discovery in databases (KDD) relies heavily on similarity queries, i.e. range queries or nearest neighbor queries, in multidimensional feature spaces. Many KDD algorithms perform a similarity query for each point stored in the database. This approach causes serious performance degenerations if the considered data set does not fit into main memory. Usual cache strategies such as LRU fail because the locality of KDD algorithms is typically not high enough… CONTINUE READING
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