A clustering index method and system based on locality-sensitive hashing
A locally sensitive hashing and indexing system technology, applied in the field of information filtering, can solve the problems of randomness limitation in hash function selection, increase in query matching speed, uneven distribution of data points, etc., to achieve improved accuracy, improved query efficiency, Query the effect of stable performance
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[0051] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.
[0052]The traditional search matching strategy adopts a tree index structure, and the search speed is faster when the data dimension is low, but even the search speed is not as good as the linear search when the dimension is greater than ten. The LSH method maps similar data points to the same hash bucket, calculates the hash value of the query point when matching, uses the point in the hash bucket with the same hash value as a candidate point, and calculates the candidate point and query point The Euclidean distance between them returns the computed nearest neighbor. The LSH method guarantees to return the real nearest neighbor point with a certain probability through the method of hash function mapping, thus great...
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