jaccard.go

package edlib

import (
	"strings"
)

// JaccardSimilarity compute the jaccard similarity coeffecient between two strings
// Takes two strings as parameters, a split length which define the k-gram single length
// (if zero split string on whitespaces) and return an index.
func JaccardSimilarity(str1, str2 string, splitLength int) float32 {
	if str1 == "" || str2 == "" {
		return 0
	}

	// Split string before rune conversion for jaccard calculation
	// If splitLength == 0 then split on whitespaces
	// Else use shingle algorithm
	var splittedStr1, splittedStr2 []string
	if splitLength == 0 {
		splittedStr1 = strings.Split(str1, " ")
		splittedStr2 = strings.Split(str2, " ")
	} else {
		splittedStr1 = ShingleSlice(str1, splitLength)
		splittedStr2 = ShingleSlice(str2, splitLength)
	}

	// Conversion of splitted string into rune array
	runeStr1 := make([][]rune, len(splittedStr1))
	for i, str := range splittedStr1 {
		runeStr1[i] = []rune(str)
	}
	runeStr2 := make([][]rune, len(splittedStr2))
	for i, str := range splittedStr2 {
		runeStr2[i] = []rune(str)
	}

	// Create union keywords slice between input strings
	unionStr := union(splittedStr1, splittedStr2)
	jacc := float32(len(runeStr1) + len(runeStr2) - len(unionStr))

	return jacc / float32(len(unionStr))
}