Solving similarity joins and range queries in metric spaces with the list of twin clusters

DOI10.1016/J.JDA.2008.09.012zbMath1162.68013OpenAlexW2122829408MaRDI QIDQ1013069

Rodrigo Paredes, Nora Reyes

Publication date: 16 April 2009

Published in: Journal of Discrete Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jda.2008.09.012

zbMATH Keywords

general metric spacesindexing methodssimilarity joins

Mathematics Subject Classification ID

Searching and sorting (68P10) Database theory (68P15)

Related Items (1)

On efficient \( k\)-optimal-location-selection query processing in metric spaces

Uses Software

• DIMACS
• LibMetricSpace

Cites Work

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• Satisfying general proximity/similarity queries with metric trees
• Fixed queries array: A fast and economical data structure for proximity searching
• Foundations of multidimensional and metric data structures.
• Similarity search. The metric space approach.
• Some approaches to best-match file searching
• A Data Structure and an Algorithm for the Nearest Point Problem
• A vector space model for automatic indexing
• Dynamic spatial approximation trees
• Practical Construction of k-Nearest Neighbor Graphs in Metric Spaces
• On the Least Cost for Proximity Searching in Metric Spaces
• Spatial Selection of Sparse Pivots for Similarity Search in Metric Spaces
• Computational Science – ICCS 2005

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