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GPH: Similarity Search in Hamming Space
2018
2018 IEEE 34th International Conference on Data Engineering (ICDE)
A similarity search in Hamming space finds binary vectors whose Hamming distances are no more than a threshold from a query vector. It is a fundamental problem in many applications, including image retrieval, near-duplicate Web page detection, and machine learning. State-of-the-art approaches to answering such queries are mainly based on the pigeonhole principle to generate a set of candidates and then verify them. We observe that the constraint based on the pigeonhole principle is not always
doi:10.1109/icde.2018.00013
dblp:conf/icde/QinWXWLI18
fatcat:culbmr66hjfdfa7rgnbloynfxu