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• W2120058970 abstract "This paper offers a novel look at using a dimensionality-reduction technique called simhash to detect similar document pairs in large-scale collections. We show that this algorithm produces interesting intermediate data, which is normally discarded, that can be used to predict which of the bits in the final hash are more susceptible to being flipped in similar documents. This paves the way for a probabilistic search technique in the Hamming space of simhashes that can be significantly faster and more space-efficient than the existing simhash approaches. We show that with 95% recall compared to deterministic search of prior work, our method exhibits 4-14 times faster lookup and requires 2-10 times less RAM on our collection of 70M web pages." @default.
• W2120058970 created "2016-06-24" @default.
• W2120058970 creator A5076734500 @default.
• W2120058970 creator A5085002707 @default.
• W2120058970 date "2011-01-01" @default.
• W2120058970 modified "2023-09-23" @default.
• W2120058970 title "Probabilistic near-duplicate detection using simhash" @default.
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• W2120058970 doi "https://doi.org/10.1145/2063576.2063737" @default.
• W2120058970 hasPublicationYear "2011" @default.
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