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Implementation method "Get all rows with Levenshtein distance less than X"

I am wondering if an effective data structure is needed to execute "Extract all rows with levenshtein spacing less than X".

A few things that interest me:

  • The explanation of the algorithm.
  • Is there an existing implementation in existing langauge database / programming?
  • Paper / article that I can refer to?
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2 answers

this is the search for the nearest neighbor in a metric space with levenshtein distance as a function of metric (or distance)

a VP-tree is one way to solve this problem

this Python VP-tree implementation is a working demo showing how the VP-tree tree works, say, in the list of words that it provides an interactive shell in which you enter a word and returns words in this list that are no more than distance X from the word you entered

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It sounds like a simple breadth-first search with each generation being just one “edit” from the previous one — and with in-place checks, make sure the string is displayed at the same level.

This would be easily implemented with a pair of hash sets / hash tables in a couple of loops.

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