Unsupervised binary code learning for approximate nearest neighbor search in large-scale datasets
Nearest neighbor search is an important operation whose goal is to find items in the dataset that are similar to a given query. It has a number of applications such as content based image retrieval (CBIR), near duplicate image detection and recommender systems. With the rapid development of the Internet and digital devices, it becomes easy to share and collect data. Taking a modern social network as an example, Facebook was reported in 2012 to be collecting more than 500 terabytes of text, images and videos each day. Conventional nearest neighbor search using linear scan becomes prohibitive when ...
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