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44 lines
1.3 KiB
JavaScript
44 lines
1.3 KiB
JavaScript
/* The Levenshtein distance (a.k.a edit distance) is a
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measure of similarity between two strings. It is
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defined as the minimum number of changes required to
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convert string a into string b (this is done by
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inserting, deleting or replacing a character in
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string a).
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The smaller the Levenshtein distance,
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the more similar the strings are. This is a very
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common problem in the application of Dynamic Programming.
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*/
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const levenshteinDistance = (a, b) => {
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// Declaring array 'D' with rows = len(a) + 1 and columns = len(b) + 1:
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const distanceMatrix = Array(b.length + 1)
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.fill(null)
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.map(() => Array(a.length + 1).fill(null))
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// Initializing first column:
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for (let i = 0; i <= a.length; i += 1) {
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distanceMatrix[0][i] = i
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}
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// Initializing first row:
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for (let j = 0; j <= b.length; j += 1) {
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distanceMatrix[j][0] = j
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}
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for (let j = 1; j <= b.length; j += 1) {
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for (let i = 1; i <= a.length; i += 1) {
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const indicator = a[i - 1] === b[j - 1] ? 0 : 1
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// choosing the minimum of all three, vis-a-vis:
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distanceMatrix[j][i] = Math.min(
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distanceMatrix[j][i - 1] + 1, // deletion
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distanceMatrix[j - 1][i] + 1, // insertion
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distanceMatrix[j - 1][i - 1] + indicator // substitution
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)
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}
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}
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return distanceMatrix[b.length][a.length]
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}
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export { levenshteinDistance }
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