Find Similar Things Fast: How Hashing Speeds Search
Looking for photos, songs or records that look alike in a huge pile is slow, but hashing makes it quick. Instead of checking every item, items get turned into short codes so the system only compares those codes — much faster and it still finds things that are close. There are two big ways to make these codes. One way makes codes without peeking at the data, called locality sensitive hashing, it try to keep similar items sharing codes. Another way learns codes from the data itself, named learning to hash, and it can tune the codes to fit real examples better. Both aim at similarity search in large collections, and both trade a little exactness for huge speed gains. People use them when exact search is too slow, l…
Find Similar Things Fast: How Hashing Speeds Search
Looking for photos, songs or records that look alike in a huge pile is slow, but hashing makes it quick. Instead of checking every item, items get turned into short codes so the system only compares those codes — much faster and it still finds things that are close. There are two big ways to make these codes. One way makes codes without peeking at the data, called locality sensitive hashing, it try to keep similar items sharing codes. Another way learns codes from the data itself, named learning to hash, and it can tune the codes to fit real examples better. Both aim at similarity search in large collections, and both trade a little exactness for huge speed gains. People use them when exact search is too slow, like in images or sounds. The idea is simple, yet powerful, and it help find what you want in seconds, where before it might take minutes or hours.
Read article comprehensive review in Paperium.net: Hashing for Similarity Search: A Survey
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