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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Permutation-Based Pruning for Approximate K-NN Search
verfasst von : Hisham Mohamed, Stéphane Marchand-Maillet
Erschienen in: Database and Expert Systems Applications
Verlag: Springer Berlin Heidelberg
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In this paper, we propose an effective indexing and search algorithms for approximate K-NN based on an enhanced implementation of the Metric Suffix Array and Permutation-Based Indexing. Our main contribution is to propose a sound scalable strategy to prune objects based on the location of the reference objects in the query ordered lists. We study the performance and efficiency of our algorithms on large-scale dataset of millions of documents. Experimental results show a decrease of computational time while preserving the quality of the results.