Java实现敏感词过滤

程序界小强 2016-04-18

java string static exception hashmap

1.读取敏感数据,构建DFA算法

package com.iris.nsonline.nsoweb.utils;

import java.io.BufferedReader;
import java.io.InputStream;
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
 * @Project:test
 * @version 1.0
 */
public class SensitiveWordInit {
	private static final String ENCODING = "UTF-8"; // 字符编码

	public static final String PATH = "/config/filterWord.txt";

	@SuppressWarnings("rawtypes")
	public HashMap sensitiveWordMap;
	
	public SensitiveWordInit(){
		super();
	}
	
	/**
	 * @version 1.0
	 */
	@SuppressWarnings("rawtypes")
	public Map initKeyWord(){
		try {
			// 读取敏感词库
			Set<String> keyWordSet = readSensitiveWordFile();
			// 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:<br>
	 * 中 = { isEnd = 0 国 = {<br>
	 * 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
	 * } } } }
	 * 
	 * @param keyWordSet
	 *            敏感词库
	 * @version 1.0
	 */
	@SuppressWarnings({ "rawtypes", "unchecked" })
	private void addSensitiveWordToHashMap(Set<String> keyWordSet) {
		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<String, String> newWorMap = null;
		// 迭代keyWordSet
		Iterator<String> iterator = 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<String,String>();
					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
	 * 
	 * @return
	 * @version 1.0
	 * @throws Exception
	 */
	@SuppressWarnings("resource")
	private Set<String> readSensitiveWordFile() throws Exception{
		Set<String> set = null;
		InputStreamReader read = null;
		try {
			if (PATH != null && !"".equals(PATH)) { // 文件流是否存在
				set = new HashSet<String>();
				InputStream in = FilterSensitiveWord.class.getResourceAsStream(PATH);
				read = new InputStreamReader(in, ENCODING);// 考虑到编码格式
				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;
	}
}

2.敏感词过滤

package com.iris.nsonline.nsoweb.utils;

import java.util.HashSet;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;

/**
 * @Description: 敏感词过滤
 * @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<String> getSensitiveWord(String txt, int matchType) {
		Set<String> sensitiveWordList = new HashSet<String>();
		
		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
	 * 
	 * @param txt
	 * @param matchType
	 * @param replaceChar
	 *            替换字符,默认*
	 * @version 1.0
	 */
	public String replaceSensitiveWord(String txt, int matchType, String replaceChar) {
		String resultTxt = txt;
		Set<String> set = getSensitiveWord(txt, matchType); // 获取所有的敏感词
		Iterator<String> iterator = 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;
	}
	
	/**
	 * 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;
	}
	
	/**
	 * 检查文字中是否包含敏感字符,检查规则如下:<br>
	 * 
	 * @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;
	}
	
	/**
	 * action调用 方法说明
	 * 
	 * @author yxs
	 * @since 2016年4月18日
	 * @param word
	 * @return
	 */
	public static String SensitivewordFilterHandler(String word) {
		SensitivewordFilter filter = new SensitivewordFilter();
		String result = "";
		if (word != null) {
			result = filter.replaceSensitiveWord(word, maxMatchType, "*");
		}
		return result;
	}

	public static void main(String[] args) {
		SensitivewordFilter filter = new SensitivewordFilter();
		System.out.println("敏感词的数量:" + filter.sensitiveWordMap.size());
		String string = "难过就躺在某一个人的怀里尽情的阐述心扉或者手机卡复制器一个人一杯红酒一部电影在夜三级片 深人静的晚上,关上电话静静的发呆着。你是中国复兴党,中国人民 万岁";
		System.out.println("待检测语句字数:" + string.length());
		long beginTime = System.currentTimeMillis();
		Set<String> set = filter.getSensitiveWord(string, 1);
		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));

		System.out.println(SensitivewordFilterHandler(string));

	}
}


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