Flask接口签名sign原理与实例代码浅析
300
2022-11-24
基于java实现DFA算法代码实例
DFA简介
DFA全称为:Deterministic Finite Automaton,即确定有穷自动机。(自己百度吧)
直接代码:
敏感词实体类
package com.nopsmile.dfa;
public class Keywords {
private String pid;
private String Content;
public Keywords() {
}
public Keywords(String content) {
super();
Content = content;
}
public String getContent() {
return Content;
}
public void setContent(String content) {
Content = content;
}
public String getPid() {
return pid;
}
public void setPid(String pid) {
this.pid = pid;
}
}
敏感词库初始化
package com.nopsmile.dfa;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;
/**
* 敏感词库初始化
*
*/
public class SensitiveWordInit{
/**
* 敏感词库
*/
public HashMap sensitiveWordMap;
/**
* 初始化敏感词 keywords
*/
public Map initKeyWord(List
try {
// 从敏感词集合对象中取出敏感词并封装到Set集合中
Set
for (Keywords s : sensitiveWords) {
keyWordSet.add(s.getContent().trim());
}
// 将敏感词库加入到HashMap中
addSensitiveWordToHashMap(keyWordSet);
} catch (Exception e) {
e.printStackTrace();
}
return sensitiveWordMap;
}
/**
* 封装敏感词库
*/
private void addSensitiveWordToHashMap(Set
// 初始化HashMap对象并控制容器的大小
sensitiveWordMap = new HashMap(keyWordSet.size());
// 敏感词
String key = null;
// 用来按照相应的格式保存敏感词库数据
Map nowMap = null;
// 用来辅助构建敏感词库
Map
// 使用一个迭代器来循环敏感词集合
Iterator
while (iterator.hasNext()) {
key = iterator.next();
// 等于敏感词库,HashMap对象在内存中占用的是同一个地址,所以此nowMap对象的变化,sensitiveWordMap对象也会跟着改变
nowMap = sensitiveWordMap;
for (int i = 0; i < key.length(); i++) {
// 截取敏感词当中的字,在敏感词库中字为HashMap对象的Key键值
char keyChar = key.charAt(i);
// 判断这个字是否存在于敏感词库中
Object wordMap = nowMap.get(keyChar);
if (wordMap != null) {
nowMap = (Map) wordMap;
} else {
newWorMap = new HashMap
newWorMap.put("isEnd", "0");
nowMap.put(keyChar, newWorMap);
nowMap = newWorMap;
}
// 如果该字是当前敏感词的最后一个字,则标识为结尾字
if (i == key.length() - 1) {
nowMap.put("isEnd", "1");
}
}
}
}
}
自定义的工具类
package com.nopsmile.dfa;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Set;
import com.alibaba.fastjson.JSONArray;
import net.sf.json.JSONObject;
/**
* 敏感词过滤工具类
*
* @author AlanLee
*
*/
public class SensitivewordUtils {
/**
* 敏感词库
*/
public static Map sensitiveWordMap = null;http://
/**
* 只过滤最小敏感词
*/
public static int minMatchTYpe = 1;
/**
* 过滤所有敏感词
*/
public static int maxMatchType = 2;
/**
* 敏感词库敏感词数量
*
* @return
*/
public static int getWordSize() {
if (SensitivewordUtils.sensitiveWordMap == null) {
return 0;
}
return SensitivewordUtils.sensitiveWordMap.size();
}
/**
* 是否包含敏感词
*
*/
public static boolean isContaintSensitiveWord(String txt, int matchType) {
boolean flag = false;
for (int i = 0; i < txt.length(); i++) {
int matchFlag = checkSensitiveWord(txt, i, matchType);
if (matchFlag > 0) {
flag = true;
}
}
return flag;
}
/**
* 获取敏感词内容
*
* @param txt
* @param matchType
* @return 敏感词内容
*/
public static Set
Set
for (int i = 0; i < txt.length(); i++) {
int length = checkSensitiveWord(txt, i, matchType);
if (length > 0) {
// 将检测出的敏感词保存到集合中
sensitiveWordList.add(txt.substring(i, i + length));
i = i + length - 1;
}
}
return sensitiveWordList;
}
/**
* 替换敏感词
*
*/
public static String replaceSensitiveWord(String txt, int matchType, String replaceChar) {
String resultTxt = txt;
Set
Iterator
String word = null;
String replaceString = null;
while (iterator.hasNext()) {
word = iterator.next();
replaceString = getReplaceChars(replaceChar, word.length());
resultTxt = resultTxt.replaceAll(word, replaceString);
}
return resultTxt;
}
/**
* 替换敏感词内容
*
*/
private static String getReplaceChars(String replaceChar, int length) {
String resultReplace = replaceChar;
for (int i = 1; i < length; i++) {
resultReplace += replaceChar;
}
return resultReplace;
}
/**
* 检查敏感词数量
*
*/
public static int checkSensitiveWord(String txt, int beginIndex, int matchType) {
boolean flag = false;
// 记录敏感词数量
int matchFlag = 0;
char word = 0;
Map nowMap = SensitivewordUtils.sensitiveWordMap;
for (int i = beginIndex; i < txt.length(); i++) {
word = txt.charAt(i);
// 判断该字是否存在于敏感词库中
nowMap = (Map) nowMap.get(word);
if (nowMap != null) {
matchFlag++;
// 判断是否是敏感词的结尾字,如果是结尾字则判断是否继续检测
if ("1".equals(nowMap.get("isEnd"))) {
flag = true;
// 判断过滤类型,如果是小过滤则跳出循环,否则继续循环
if (SensitivewordUtils.minMatchTYpe == matchType) {
break;
}
}
} else {
break;
}
}
if (!flag) {
matchFlag = 0;
}
return matchFlag;
}
/**
* 敏感词汇对应个数
* 返回 "关键字"="关键字个数"
*
*/
public static Map getSensitiveWordSum(String txt, int matchType) {
Map
for (int i = 0; i < txt.length(); i++) {
int nZrGQWlength = checkSensitiveWord(txt, i, matchType);
if (length > 0) {
// 将检测出的敏感词保存到集合中
String str=txt.substring(i, i + length);
if(map.containsKey(str)) {
map.put(str, map.get(str).intValue()+1);
}else {
map.put(str, new Integer(1));
}
//System.out.println(txt.substring(i, i + length));
i = i + length - 1;
}
}
return map;
}
/**
* 对map数组value排序,并取前10
* this method will always sort the map;
* isCondition is true condition can be used otherwise invalid
* @param unsortMap
* @return
*/
public static Map
// 1. Convert Map to List of Map
List
new LinkedList
// 2. Sort list with Collections.sort(), provide a custom Comparator
// Try switch the o1 o2 position for a different order
Collections.sort(list, new Comparator
public int compare(Map.Entry
Map.Entry
return (o2.getValue()).compareTo(o1.getValue());
}
});
// 3. Loop the sorted list and put it into a new insertion order Map LinkedHashMap
Map
if(isCondition) {
for (int i = 0; i < list.sihttp://ze(); i++) {
if (i < condition) {
sortedMap.put(list.get(i).getKey(), list.get(i).getValue());
}
}
}else{
for (int i = 0; i < list.size(); i++) {
sortedMap.put(list.get(i).getKey(), list.get(i).getValue());
}
}
return sortedMap;
}
}
使用上面类流程代码
Keywords ss=new Keywords("好");
List linZrGQWst = new ArrayList();
list.add(ss);
SensitiveWordInit sensitiveWordInit = new SensitiveWordInit();
Map sensitiveWordMap = sensitiveWordInit.initKeyWord(list);
// 传入SensitivewordEngine类中的敏感词库
SensitivewordUtils.sensitiveWordMap = sensitiveWordMap;
SensitivewordUtils.getSensitiveWordSum("需要检测的文本", 2) ;
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