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
下面是一个不依赖于任何库的快速解决方案，并且可以很好地处理自动完成表单之类的事情:
function compare_strings(str1, str2) {
arr1 = str1.split("");
arr2 = str2.split("");
res = arr1.reduce((a, c) => a + arr2.includes(c), 0);
return(res)
}
可以像这样在自动完成输入中使用:
HTML:
<div id="wrapper">
<input id="tag_input" placeholder="add tags..."></input>
<div id="hold_tags"></div>
</div>
CSS:
body {
background: #2c2c54;
display: flex;
justify-content: center;
align-items: center;
}
input {
height: 40px;
width: 400px;
border-radius: 4px;
outline: 0;
border: none;
padding-left: 5px;
font-size: 18px;
}
#wrapper {
height: auto;
background: #40407a;
}
.tag {
background: #ffda79;
margin: 4px;
padding: 5px;
border-radius: 4px;
box-shadow: 2px 2px 2px black;
font-size: 18px;
font-family: arial;
cursor: pointer;
}
JS:
const input = document.getElementById("tag_input");
const wrapper = document.getElementById("wrapper");
const hold_tags = document.getElementById("hold_tags");
const words = [
"machine",
"data",
"platform",
"garbage",
"twitter",
"knowledge"
];
input.addEventListener("input", function (e) {
const value = document.getElementById(e.target.id).value;
hold_tags.replaceChildren();
if (value !== "") {
words.forEach(function (word) {
if (compare_strings(word, value) > value.length - 1) {
const tag = document.createElement("div");
tag.className = "tag";
tag.innerText = word;
hold_tags.append(tag);
}
});
}
});
function compare_strings(str1, str2) {
arr1 = str1.split("");
arr2 = str2.split("");
res = arr1.reduce((a, c) => a + arr2.includes(c), 0);
return res;
}
结果:
其他回答
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!
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。
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)
}
如果输入数据太大(比如数百万个字符串)，这个问题就很难实现。我用弹性搜索来解决这个问题。
快速入门:https://www.elastic.co/guide/en/elasticsearch/client/net-api/6.x/elasticsearch-net.html
只需将所有输入数据插入到DB中，您就可以根据任何编辑距离快速搜索任何字符串。下面是一个c#代码片段，它会给你一个按编辑距离排序的结果列表(从小到大)
var res = client.Search<ClassName>(s => s
.Query(q => q
.Match(m => m
.Field(f => f.VariableName)
.Query("SAMPLE QUERY")
.Fuzziness(Fuzziness.EditDistance(5))
)
));
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/
