I already have the algorithm to produce locality-sensitive hashes, but how should I bucket them to take advantage of their characteristics(i.e. similar elements have near hashes(with the hamming dista
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I currently have a reddit-clone type website. I\'m trying to recommend posts based on the posts that my users have previously liked.
Given a n*n matrix and a value k, how do we find all the neighbors for each element? for example: in a 4*4 matrix, with k=2
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I have a set of words (a \'dictionary\'), and I have to find the closest word from the dictionary, given a new word. (I am using \'word\' as a keyword, as it is actually a variable length sequence of
I have asked a question a few days back on how to find the nearest neighbors for a given vector. My vector is now 21 dimensions and before I proceed further, because I am not from the domain of Machin
i am trying to build a procedure to obtain k nearest neighbor points to a point with a selected ID. I need to do this without using any spatial locator features like sdo_geometry or nn.
I\'ve got a recursive function (on tree) and I need to make it work without recursion and representing the tree as an implicit data structure (array).
I have for example a coordinate: 41,791063, 12,6923072 and I want to find the nearest node in the OSM DB
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