High Dimensional Similarity Joins: Algorithms and Performance Evaluation

@article{Koudas2000HighDS,
  title={High Dimensional Similarity Joins: Algorithms and Performance Evaluation},
  author={N. Koudas and K. Sevcik},
  journal={IEEE Trans. Knowl. Data Eng.},
  year={2000},
  volume={12},
  pages={3-18}
}
  • N. Koudas, K. Sevcik
  • Published 2000
  • Computer Science
  • IEEE Trans. Knowl. Data Eng.
  • Current data repositories include a variety of data types, including audio, images, and time series. State-of-the-art techniques for indexing such data and doing query processing rely on a transformation of data elements into points in a multidimensional feature space. Indexing and query processing then take place in the feature space. We study algorithms for finding relationships among points in multidimensional feature spaces, specifically algorithms for multidimensional joins. Like joins of… CONTINUE READING
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