Java实现敏感词过滤
我是首先借鉴这个文章的，理论部分就看这个 http://blog.csdn.net/chenssy/article/details/26961957
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStreamReader;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;
/**
* @Description: 初始化敏感词库，将敏感词加入到HashMap中，构建DFA算法模型
* @author 刘赖春
* @version 1.0
*
*/
public class SensitiveWordInit {
private String ENCODING ="GBK" ; //字符编码
@SuppressWarnings("rawtypes")
public HashMap sensitiveWordMap;
public SensitiveWordInit(){
super();
}
@SuppressWarnings("rawtypes")
public Map initKeyWord(){
try {
//读取敏感词库
Set
//将敏感词库加入到HashMap中
addSensitiveWordToHashMap(keyWordSet);
//spring获取application，然后application.setAttribute("sensitiveWordMap",sensitiveWordMap);
} catch (Exception e) {
e.printStackTrace();
}
return sensitiveWordMap;
}
/**
* 读取敏感词库，将敏感词放入HashSet中，构建一个DFA算法模型：
* 中 = {
* isEnd = 0
* 国 = {
* isEnd = 1
* 人 = {isEnd = 0
* 民 = {isEnd = 1}
* }
* 男 = {
* isEnd = 0
* 人 = {
* isEnd = 1
* }
* }
* }
* }
* 五 = {
* isEnd = 0
* 星 = {
* isEnd = 0
* 红 = {
* isEnd = 0
* 旗 = {
* isEnd = 1
* }
* }
* }
* }
*/
@SuppressWarnings({ "rawtypes", "unchecked" })
private void addSensitiveWordToHashMap(Set
sensitiveWordMap = new HashMap(keyWordSet.size()); //初始化敏感词容器，减少扩容操作
String key = null;
Map nowMap = null;
Map
//迭代keyWordSet
Iterator
while(iterator.hasNext()){
key = iterator.next(); //关键字
nowMap = sensitiveWordMap;
for(int i = 0 ; i < key.length() ; i++){
char keyChar = key.charAt(i); //转换成char型
Object wordMap = nowMap.get(keyChar); //获取
if(wordMap != null){ //如果存在该key，直接赋值
nowMap = (Map) wordMap;
}
else{ //不存在则，则构建一个map，同时将isEnd设置为0，因为他不是最后一个
newWorMap = new HashMap
newWorMap.put("isEnd", "0"); //不是最后一个
nowMap.put(keyChar, newWorMap);
nowMap = newWorMap;
}
if(i == key.length() - 1){
nowMap.put("isEnd", "1"); //最后一个
}
}
}
}
/**
* 读取敏感词库中的内容，将内容添加到set集合中
*/
@SuppressWarnings("resource")
private Set
Set
String t=Thread.currentThread().getContextClassLoader().getResource("").getPath()+"\\com\\risenb\\util\\";
File file = new File(t+"SensitiveWord.txt"); //读取文件
InputStreamReader read = new InputStreamReader(new FileInputStream(file),ENCODING);
try {
if(file.isFile() && file.exists()){ //文件流是否存在
set = new HashSet
BufferedReader bufferedReader = new BufferedReader(read);
String txt = null;
while((txt = bufferedReader.readLine()) != null){ //读取文件，将文件内容放入到set中
set.add(txt);
}
}
else{ //不存在抛出异常信息
throw new Exception("敏感词库文件不存在");
}
} catch (Exception e) {
throw e;
}finally{
read.close(); //关闭文件流
}
return set;
}
}
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import java.util.HashSet;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;
/**
* 过滤敏感词
* @author 刘赖春
* @Date 2017-3-31 9:24
* @version 1.0
*/
public class SensitivewordFilter {
@SuppressWarnings("rawtypes")
private Map sensitiveWordMap=null;
public static int minMatchTYpe = 1; //最小匹配规则
public static int maxMatchType = 2; //最大匹配规则
/**
* 构造函数，初始化敏感词库
*/
public SensitivewordFilter(){
sensitiveWordMap = new SensitiveWordInit().initKeyWord();
}
/**
* 判断文字是否包含敏感字符
* @param txt 文字
* @param matchType 匹配规则 1：最小匹配规则，2：最大匹配规则
* @return 若包含返回true，否则返回false
* @version 1.0
*/
public boolean isContaintSensitiveWord(String txt,int matchType){
boolean flag = false;
for(int i = 0 ; i < txt.length() ; i++){
int matchFlag = this.CheckSensitiveWord(txt, i, matchType); //判断是否包含敏感字符
if(matchFlag > 0){ //大于0存在，返回true
flag = true;
}
}
return flag;
}
/**
* 获取文字中的敏感词
* @param txt 文字
* @param matchType 匹配规则 1：最小匹配规则，2：最大匹配规则
* @return
* @version 1.0
*/
public Set
Set
for(int i = 0 ; i < txt.length() ; i++){
int length = CheckSensitiveWord(txt, i, matchType); //判断是否包含敏感字符
if(length > 0){ //存在,加入list中
sensitiveWordList.add(txt.substring(i, i+length));
i = i + length - 1; //减1的原因，是因为for会自增
}
}
return sensitiveWordList;
}
/**
* 替换敏感字字符,所有的敏感词都用*替换
* @param txt 字符串的内容
* @version 1.0
*/
public String replaceSensitiveWord(String txt){
String resultTxt = txt;
Set
Iterator
String word = null;
String replaceString = null;
while (iterator.hasNext()) {
word = iterator.next();
replaceString = getReplaceChars("*", word.length());
resultTxt = resultTxt.replaceAll(word, replaceString);
}
return resultTxt;
}
/**
* @TODO 获取替换字符串
* @param replaceChar
* @param length
* @return
* @version 1.0
*/
private String getReplaceChars(String replaceChar,int length){
String resultReplace = replaceChar;
for(int i = 1 ; i < length ; i++){
resultReplace += replaceChar;
}
return resultReplace;
}
/**
* @TODO 检查文字中是否包含敏感字符，检查规则如下：
* @param txt
* @param beginIndex
* @param matchType
* @return，如果存在，则返回敏感词字符的长度，不存在返回0
* @version 1.0
*/
@SuppressWarnings({ "rawtypes"})
public int CheckSensitiveWord(String txt,int beginIndex,int matchType){
boolean flag = false; //敏感词结束标识位：用于敏感词只有1位的情况
int matchFlag = 0; //匹配标识数默认为0
char word = 0;
Map nowMap = sensitiveWordMap;
for(int i = beginIndex; i < txt.length() ; i++){
word = txt.charAt(i);
nowMap = (Map) nowMap.get(word); //获取指定key
if(nowMap != null){ //存在，则判断是否为最后一个
matchFlag++; //找到相应key，匹配标识+1
if("1".equals(nowMap.get("isEnd"))){ //如果为最后一个匹配规则,结束循环，返回匹配标识数
flag = true; //结束标志位为true
if(SensitivewordFilter.minMatchTYpe == matchType){ //最小规则，直接返回,最大规则还需继续查找
break;
}
}
}
else{ //不存在，直接返回
break;
}
}
if(matchFlag < 2 || !flag){ //长度必须大于等于1，为词
matchFlag = 0;
}
return matchFlag;
}
public static void main(String[] args) {
long beginTime = System.currentTimeMillis();
SensitivewordFilter filter = new SensitivewordFilter();
System.out.println("敏感词的数量：" + filter.sensitiveWordMap.size());
String string = "腐败125"
+ "公关兼职招聘4, 傻逼5，大 傻 逼123";
System.out.println("待检测语句字数：" + string.length());
Set
String str= filter.replaceSensitiveWord(string);//替换
System.out.println("替换后的："+str);
long endTime = System.currentTimeMillis();
System.out.println("语句中包含敏感词的个数为：" + set.size() + "。包含：" + set);
System.out.println("总共消耗时间为：" + (endTime - beginTime));
}
}
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