Abstract
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. In this paper, we introduce the novel problem of co-hashing where both documents and terms are hashed simultaneously according to their semantic similarities. Furthermore, we propose a novel algorithm Laplacian Co-Hashing (LCH) to solve this problem which directly optimises the Hamming distance. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Zhang, D., Wang, J., Cai, D., & Lu, J. (2010). Laplacian co-hashing of terms and documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 577–580). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_51
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