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Locality Sensitive Hashing (LSH) is proposed to construct indexes for high-dimensional approximate similarity search. Multi-Probe LSH (MPLSH) is a variation of LSH which can reduce the number of hash tables. Based on the idea of MPLSH, this paper proposes a novel probability model and a query-adaptive algorithm to generate the optimal multi-probe sequence for range queries. Our probability model takes...
Constructing effective and efficient indexes for explosive growing multimedia data is a very challenging problem. To solve the problem, Haghani et al. provide a distributed similarity search method in high dimensions using Locality Sensitive Hashing. However, their method needs to estimate a global parameter on the whole dataset beforehand. It is impractical for a large-scale dynamical dataset. This...
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