我需要一种方法来比较多个字符串到一个测试字符串，并返回与它非常相似的字符串:
TEST STRING: THE BROWN FOX JUMPED OVER THE RED COW
CHOICE A : THE RED COW JUMPED OVER THE GREEN CHICKEN
CHOICE B : THE RED COW JUMPED OVER THE RED COW
CHOICE C : THE RED FOX JUMPED OVER THE BROWN COW
(如果我做对了)最接近“TEST string”的字符串应该是“CHOICE C”。最简单的方法是什么?
我计划将其实现为多种语言，包括VB.net、Lua和JavaScript。此时，伪代码是可以接受的。如果你能提供一个特定语言的例子，这也是非常感谢的!
当前回答
这里你可以有一个golang POC来计算给定单词之间的距离。您可以为其他作用域调整minDistance和difference。
操场上:https://play.golang.org/p/NtrBzLdC3rE
package main
import (
"errors"
"fmt"
"log"
"math"
"strings"
)
var data string = `THE RED COW JUMPED OVER THE GREEN CHICKEN-THE RED COW JUMPED OVER THE RED COW-THE RED FOX JUMPED OVER THE BROWN COW`
const minDistance float64 = 2
const difference float64 = 1
type word struct {
data string
letters map[rune]int
}
type words struct {
words []word
}
// Print prettify the data present in word
func (w word) Print() {
var (
lenght int
c int
i int
key rune
)
fmt.Printf("Data: %s\n", w.data)
lenght = len(w.letters) - 1
c = 0
for key, i = range w.letters {
fmt.Printf("%s:%d", string(key), i)
if c != lenght {
fmt.Printf(" | ")
}
c++
}
fmt.Printf("\n")
}
func (ws words) fuzzySearch(data string) ([]word, error) {
var (
w word
err error
founds []word
)
w, err = initWord(data)
if err != nil {
log.Printf("Errors: %s\n", err.Error())
return nil, err
}
// Iterating all the words
for i := range ws.words {
letters := ws.words[i].letters
//
var similar float64 = 0
// Iterating the letters of the input data
for key := range w.letters {
if val, ok := letters[key]; ok {
if math.Abs(float64(val-w.letters[key])) <= minDistance {
similar += float64(val)
}
}
}
lenSimilarity := math.Abs(similar - float64(len(data)-strings.Count(data, " ")))
log.Printf("Comparing %s with %s i've found %f similar letter, with weight %f", data, ws.words[i].data, similar, lenSimilarity)
if lenSimilarity <= difference {
founds = append(founds, ws.words[i])
}
}
if len(founds) == 0 {
return nil, errors.New("no similar found for data: " + data)
}
return founds, nil
}
func initWords(data []string) []word {
var (
err error
words []word
word word
)
for i := range data {
word, err = initWord(data[i])
if err != nil {
log.Printf("Error in index [%d] for data: %s", i, data[i])
} else {
words = append(words, word)
}
}
return words
}
func initWord(data string) (word, error) {
var word word
word.data = data
word.letters = make(map[rune]int)
for _, r := range data {
if r != 32 { // avoid to save the whitespace
word.letters[r]++
}
}
return word, nil
}
func main() {
var ws words
words := initWords(strings.Split(data, "-"))
for i := range words {
words[i].Print()
}
ws.words = words
solution, _ := ws.fuzzySearch("THE BROWN FOX JUMPED OVER THE RED COW")
fmt.Println("Possible solutions: ", solution)
}
其他回答
Lua实现，为子孙后代:
function levenshtein_distance(str1, str2)
local len1, len2 = #str1, #str2
local char1, char2, distance = {}, {}, {}
str1:gsub('.', function (c) table.insert(char1, c) end)
str2:gsub('.', function (c) table.insert(char2, c) end)
for i = 0, len1 do distance[i] = {} end
for i = 0, len1 do distance[i][0] = i end
for i = 0, len2 do distance[0][i] = i end
for i = 1, len1 do
for j = 1, len2 do
distance[i][j] = math.min(
distance[i-1][j ] + 1,
distance[i ][j-1] + 1,
distance[i-1][j-1] + (char1[i] == char2[j] and 0 or 1)
)
end
end
return distance[len1][len2]
end
你可能会对这篇博客感兴趣。
http://seatgeek.com/blog/dev/fuzzywuzzy-fuzzy-string-matching-in-python
Fuzzywuzzy是一个Python库，它提供了简单的距离度量，例如用于字符串匹配的Levenshtein距离。它构建在标准库中的difflib之上，并将使用Python-levenshtein(如果可用的话)的C实现。
http://pypi.python.org/pypi/python-Levenshtein/
关于这类算法，一个非常非常好的资源是Simmetrics: http://sourceforge.net/projects/simmetrics/
不幸的是，包含大量文档的很棒的网站已经消失了:( 以防它再次出现，它之前的地址是这样的: http://www.dcs.shef.ac.uk/~sam/simmetrics.html
瞧(由“时光倒流机”提供):http://web.archive.org/web/20081230184321/http://www.dcs.shef.ac.uk/~sam/simmetrics.html
你可以研究一下源代码，有几十种算法可以进行这种比较，每一种都有不同的权衡。这些实现是用Java实现的。
你可能会发现这个图书馆很有用! http://code.google.com/p/google-diff-match-patch/
目前可以在Java, JavaScript, Dart, c++， c#， Objective C, Lua和Python中使用
它也运行得很好。我在我的几个Lua项目中使用了它。
而且我认为将其移植到其他语言并不困难!
这里有一个使用c#的示例。
public static void Main()
{
Console.WriteLine("Hello World " + LevenshteinDistance("Hello","World"));
Console.WriteLine("Choice A " + LevenshteinDistance("THE BROWN FOX JUMPED OVER THE RED COW","THE RED COW JUMPED OVER THE GREEN CHICKEN"));
Console.WriteLine("Choice B " + LevenshteinDistance("THE BROWN FOX JUMPED OVER THE RED COW","THE RED COW JUMPED OVER THE RED COW"));
Console.WriteLine("Choice C " + LevenshteinDistance("THE BROWN FOX JUMPED OVER THE RED COW","THE RED FOX JUMPED OVER THE BROWN COW"));
}
public static float LevenshteinDistance(string a, string b)
{
var rowLen = a.Length;
var colLen = b.Length;
var maxLen = Math.Max(rowLen, colLen);
// Step 1
if (rowLen == 0 || colLen == 0)
{
return maxLen;
}
/// Create the two vectors
var v0 = new int[rowLen + 1];
var v1 = new int[rowLen + 1];
/// Step 2
/// Initialize the first vector
for (var i = 1; i <= rowLen; i++)
{
v0[i] = i;
}
// Step 3
/// For each column
for (var j = 1; j <= colLen; j++)
{
/// Set the 0'th element to the column number
v1[0] = j;
// Step 4
/// For each row
for (var i = 1; i <= rowLen; i++)
{
// Step 5
var cost = (a[i - 1] == b[j - 1]) ? 0 : 1;
// Step 6
/// Find minimum
v1[i] = Math.Min(v0[i] + 1, Math.Min(v1[i - 1] + 1, v0[i - 1] + cost));
}
/// Swap the vectors
var vTmp = v0;
v0 = v1;
v1 = vTmp;
}
// Step 7
/// The vectors were swapped one last time at the end of the last loop,
/// that is why the result is now in v0 rather than in v1
return v0[rowLen];
}
输出结果为:
Hello World 4
Choice A 15
Choice B 6
Choice C 8
