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Self-Taught Hashing for Fast Similarity Search
[article]
2010
arXiv
pre-print
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is semantic hashing which designs compact binary codes for a large number of documents so that semantically similar documents are mapped to similar codes (within a short Hamming distance). Although some recently proposed techniques are able to generate high-quality codes for documents known in advance, obtaining the codes
arXiv:1004.5370v1
fatcat:kmaqddklzfd5tjnrljfjepwvze