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min hash what is it and how does it work min hash also known as minwise independent permutations locality sensitive hashing scheme is a technique that can be used for efficiently estimating similarity it was invented by andrei brodar in 1997. applications include detecting duplicate web pages used by the alta vista search engine or for large scale clustering of documents based on word similarities so for some background locality sensitive hashing i first covered in a previous video but the main idea is that unlike traditional hashing where similar keys should yield completely different values locality sensitive hashing aims to cluster them into similar values as you can see on the right hand side the jacquard similarity coefficient can be used as an indicator for set similarity so included the formula down below of the jacquard index formula including an example on the right hand side if youamp;#39;re interested so we consider the following problem we have several billion documents an
