Several recent proposals have shown the feasibility of significantly speeding-up pattern matching by means of Full Search-equivalent techniques, i.e. without approximating the outcome of the search with respect to a brute force investigation. These techniques are generally heavily based on efficient incremental calculation schemes aimed at avoiding unnecessary computations. In a very recent and extensive experimental evaluation, Low Resolution Pruning turned out to be in most cases the best performing approach. In this paper we propose a computational analysis of several incremental techniques specifically designed to enhance the efficiency of LRP. In addition, we propose a novel LRP algorithm aimed at minimizing the theoretical number of operations by adaptively exploiting different incremental approaches. We demonstrate the effectiveness of our proposal by means of experimental evaluation on a large dataset.

Adaptive Low Resolution Pruning for Fast Full-Search Equivalente Pattern Matching

TOMBARI, FEDERICO;DI STEFANO, LUIGI;
2011

Abstract

Several recent proposals have shown the feasibility of significantly speeding-up pattern matching by means of Full Search-equivalent techniques, i.e. without approximating the outcome of the search with respect to a brute force investigation. These techniques are generally heavily based on efficient incremental calculation schemes aimed at avoiding unnecessary computations. In a very recent and extensive experimental evaluation, Low Resolution Pruning turned out to be in most cases the best performing approach. In this paper we propose a computational analysis of several incremental techniques specifically designed to enhance the efficiency of LRP. In addition, we propose a novel LRP algorithm aimed at minimizing the theoretical number of operations by adaptively exploiting different incremental approaches. We demonstrate the effectiveness of our proposal by means of experimental evaluation on a large dataset.
F. Tombari; W. Ouyang; L. Di Stefano; W.K. Cham
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/106135
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