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SOFSEM
2007
Springer

Fast Approximate Point Set Matching for Information Retrieval

3 years 10 months ago
Fast Approximate Point Set Matching for Information Retrieval
We investigate randomised algorithms for subset matching with spatial point sets—given two sets of d-dimensional points: a data set T consisting of n points and a pattern P consisting of m points, find the largest match for a subset of the pattern in the data set. This problem is known to be 3-SUM hard and so unlikely to be solvable exactly in subquadratic time. We present an efficient bit-parallel O(nm) time algorithm and an O(n log m) time solution based on correlation calculations using fast Fourier transforms. Both methods are shown experimentally to give answers within a few percent of the exact solution and provide a considerable practical speedup over existing deterministic algorithms.
Raphaël Clifford, Benjamin Sach
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where SOFSEM
Authors Raphaël Clifford, Benjamin Sach
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