Fast Approximate Point Set Matching for Information Retrieval

Authors:
Raphaël Clifford;Benjamin Sach
Affiliations:
University of Bristol, Department of Computer Science, Woodland Road, Bristol, BS8 1UB, UK;University of Bristol, Department of Computer Science, Woodland Road, Bristol, BS8 1UB, UK
Venue:
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Year:
2007

Citing 3
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Abstract

We investigate randomised algorithms for subset matching with spatial point sets--given two sets of d-dimensional points: a data set Tconsisting of npoints and a pattern Pconsisting of mpoints, 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(nlogm) 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.