矩陣式比較兩文字字串相似度（包含漢字）方法兩則（java程式碼）
阿新 • • 發佈：2019-01-23
package com.gsww.ctyxy.util;
import java.text.NumberFormat;
import java.util.Locale;
/**
* 比較兩個字串的相似度
*/
public class AutomaticRating {
/* public static void main(String[] args) {
String strA = "我是中國人";
String strB = "我是中國人";
double result=SimilarDegree(strA, strB);
if(result>=0.4&&result<0.6){
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--及格");
}else if (result>=0.6&&result<0.8) {
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--良好");
}else if (result>=0.8) {
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--優秀");
}else{
System.out.println("本次作業的成績為："+similarityResult(result)+result+"--不及格");
}
} */
/**
* 相似度轉百分比
*/
public static String similarityResult(double resule){
return NumberFormat.getPercentInstance(new Locale( "en ", "US ")).format(resule);
}
/**
* 相似度比較
* @param strA
* @param strB
* @return
*/
public static double SimilarDegree(String strA, String strB){
String newStrA = removeSign(strA);
//System.out.println(newStrA);
String newStrB = removeSign(strB);
//System.out.println(newStrB);
int temp = Math.max(newStrA.length(), newStrB.length());
int lenA = newStrA.length();
int lenB = newStrB.length();
System.out.println(temp);
int temp2 = 0;
//在此判斷newStrA和newStrB的長度
if (lenA >=lenB?true:false) {
temp2 = longestCommonSubstring(newStrA, newStrB).length();
}else{
temp2 = longestCommonSubstring(newStrB, newStrA).length();
}
System.out.println(temp2);
return temp2 * 1.0 / temp;
}
private static String removeSign(String str) {
StringBuffer sb = new StringBuffer();
for (char item : str.toCharArray())
if (charReg(item)){
System.out.println("--"+item);
sb.append(item);
}
System.out.println(sb.toString());
return sb.toString();
}
//利用正則表示式來解析字串
private static boolean charReg(char charValue) {
return (charValue >= 0x4E00 && charValue <= 0X9FA5)
|| (charValue >= 'a' && charValue <= 'z')
|| (charValue >= 'A' && charValue <= 'Z')
|| (charValue >= '0' && charValue <= '9');
}
//解析兩個字串的相同部分的長度，返回公共部分，strA字串長度 > strB字串
private static String longestCommonSubstring(String strA, String strB) {
char[] chars_strA = strA.toCharArray();
char[] chars_strB = strB.toCharArray();
int m = chars_strA.length;
int n = chars_strB.length;
int[][] matrix = new int[m + 1][n + 1];
for (int i = 1; i <= m; i++) {
for (int j = 1; j <= n; j++) {
if (chars_strA[i - 1] == chars_strB[j - 1])
matrix[i][j] = matrix[i - 1][j - 1] + 1;
else
matrix[i][j] = Math.max(matrix[i][j - 1], matrix[i - 1][j]);
}
}
char[] result = new char[matrix[m][n]];
int currentIndex = result.length - 1;
while (matrix[m][n] != 0) {
if (matrix[n] == matrix[n - 1])
n--;
else if (matrix[m][n] == matrix[m - 1][n])
m--;
else {
result[currentIndex] = chars_strA[m - 1];
currentIndex--;
n--;
m--;
}
}
return new String(result);
}
}
part 2：public class SimilarityRatio {
private int compare(String str, String target)
{
int d[][]; // 矩陣
int n = str.length();
int m = target.length();
int i; // 遍歷str的
int j; // 遍歷target的
char ch1; // str的
char ch2; // target的
int temp; // 記錄相同字元,在某個矩陣位置值的增量,不是0就是1
if (n == 0) { return m; }
if (m == 0) { return n; }
d = new int[n + 1][m + 1];
for (i = 0; i <= n; i++)
{ // 初始化第一列
d[i][0] = i;
}
for (j = 0; j <= m; j++)
{ // 初始化第一行
d[0][j] = j;
}
for (i = 1; i <= n; i++)
{ // 遍歷str
ch1 = str.charAt(i - 1);
// 去匹配target
for (j = 1; j <= m; j++)
{
ch2 = target.charAt(j - 1);
if (ch1 == ch2 || ch1 == ch2+32 || ch1+32 == ch2)
{
temp = 0;
} else
{
temp = 1;
}
// 左邊+1,上邊+1, 左上角+temp取最小
d[i][j] = min(d[i - 1][j] + 1, d[i][j - 1] + 1, d[i - 1][j - 1] + temp);
}
}
return d[n][m];
}
private int min(int one, int two, int three)
{
return (one = one < two ? one : two) < three ? one : three;
}
/**
* 獲取兩字串的相似度
*/
public float getSimilarityRatio(String str, String target)
{
//去除空白字元、換行、標點符號
String regex = "[\\pP\\p{Punct}\\s]";
return 1 - (float) compare(str.replaceAll(regex, ""), target.replaceAll(regex, "")) / Math.max(str.length(), target.length());
}
public static void main(String[] args)
{
String str= "論據容易理解,把它們分成小塊,並以相似的格式和句子結構呈現每一個論據";
String target = "根據領域關係可以合併領域相同或相似的句子，得到句群及其領域";
SimilarityRatio lt = new SimilarityRatio();
System.out.println("similarityRatio=" + lt.getSimilarityRatio(str, target));
}
}
import java.text.NumberFormat;
import java.util.Locale;
/**
* 比較兩個字串的相似度
*/
public class AutomaticRating {
/* public static void main(String[] args) {
String strA = "我是中國人";
String strB = "我是中國人";
double result=SimilarDegree(strA, strB);
if(result>=0.4&&result<0.6){
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--及格");
}else if (result>=0.6&&result<0.8) {
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--良好");
}else if (result>=0.8) {
System.out.println("本次作業的成績為：" +similarityResult(result)+result+"--優秀");
}else{
System.out.println("本次作業的成績為："+similarityResult(result)+result+"--不及格");
}
} */
/**
* 相似度轉百分比
*/
public static String similarityResult(double resule){
return NumberFormat.getPercentInstance(new Locale( "en ", "US ")).format(resule);
}
/**
* 相似度比較
* @param strA
* @param strB
* @return
*/
public static double SimilarDegree(String strA, String strB){
String newStrA = removeSign(strA);
//System.out.println(newStrA);
String newStrB = removeSign(strB);
//System.out.println(newStrB);
int temp = Math.max(newStrA.length(), newStrB.length());
int lenA = newStrA.length();
int lenB = newStrB.length();
System.out.println(temp);
int temp2 = 0;
//在此判斷newStrA和newStrB的長度
if (lenA >=lenB?true:false) {
temp2 = longestCommonSubstring(newStrA, newStrB).length();
}else{
temp2 = longestCommonSubstring(newStrB, newStrA).length();
}
System.out.println(temp2);
return temp2 * 1.0 / temp;
}
private static String removeSign(String str) {
StringBuffer sb = new StringBuffer();
for (char item : str.toCharArray())
if (charReg(item)){
System.out.println("--"+item);
sb.append(item);
}
System.out.println(sb.toString());
return sb.toString();
}
//利用正則表示式來解析字串
private static boolean charReg(char charValue) {
return (charValue >= 0x4E00 && charValue <= 0X9FA5)
|| (charValue >= 'a' && charValue <= 'z')
|| (charValue >= 'A' && charValue <= 'Z')
|| (charValue >= '0' && charValue <= '9');
}
//解析兩個字串的相同部分的長度，返回公共部分，strA字串長度 > strB字串
private static String longestCommonSubstring(String strA, String strB) {
char[] chars_strA = strA.toCharArray();
char[] chars_strB = strB.toCharArray();
int m = chars_strA.length;
int n = chars_strB.length;
int[][] matrix = new int[m + 1][n + 1];
for (int i = 1; i <= m; i++) {
for (int j = 1; j <= n; j++) {
if (chars_strA[i - 1] == chars_strB[j - 1])
matrix[i][j] = matrix[i - 1][j - 1] + 1;
else
matrix[i][j] = Math.max(matrix[i][j - 1], matrix[i - 1][j]);
}
}
char[] result = new char[matrix[m][n]];
int currentIndex = result.length - 1;
while (matrix[m][n] != 0) {
if (matrix[n] == matrix[n - 1])
n--;
else if (matrix[m][n] == matrix[m - 1][n])
m--;
else {
result[currentIndex] = chars_strA[m - 1];
currentIndex--;
n--;
m--;
}
}
return new String(result);
}
}
part 2：public class SimilarityRatio {
private int compare(String str, String target)
{
int d[][]; // 矩陣
int n = str.length();
int m = target.length();
int i; // 遍歷str的
int j; // 遍歷target的
char ch1; // str的
char ch2; // target的
int temp; // 記錄相同字元,在某個矩陣位置值的增量,不是0就是1
if (n == 0) { return m; }
if (m == 0) { return n; }
d = new int[n + 1][m + 1];
for (i = 0; i <= n; i++)
{ // 初始化第一列
d[i][0] = i;
}
for (j = 0; j <= m; j++)
{ // 初始化第一行
d[0][j] = j;
}
for (i = 1; i <= n; i++)
{ // 遍歷str
ch1 = str.charAt(i - 1);
// 去匹配target
for (j = 1; j <= m; j++)
{
ch2 = target.charAt(j - 1);
if (ch1 == ch2 || ch1 == ch2+32 || ch1+32 == ch2)
{
temp = 0;
} else
{
temp = 1;
}
// 左邊+1,上邊+1, 左上角+temp取最小
d[i][j] = min(d[i - 1][j] + 1, d[i][j - 1] + 1, d[i - 1][j - 1] + temp);
}
}
return d[n][m];
}
private int min(int one, int two, int three)
{
return (one = one < two ? one : two) < three ? one : three;
}
/**
* 獲取兩字串的相似度
*/
public float getSimilarityRatio(String str, String target)
{
//去除空白字元、換行、標點符號
String regex = "[\\pP\\p{Punct}\\s]";
return 1 - (float) compare(str.replaceAll(regex, ""), target.replaceAll(regex, "")) / Math.max(str.length(), target.length());
}
public static void main(String[] args)
{
String str= "論據容易理解,把它們分成小塊,並以相似的格式和句子結構呈現每一個論據";
String target = "根據領域關係可以合併領域相同或相似的句子，得到句群及其領域";
SimilarityRatio lt = new SimilarityRatio();
System.out.println("similarityRatio=" + lt.getSimilarityRatio(str, target));
}
}