DFA算法-简易Java敏感词过滤(含源文件和上万敏感词列表)

public class Word implements Comparable<Word>{
    public char c;
    public List next = null;
 
    public Word(char c){
        this.c = c;
    }
 
    @Override
    public int compareTo(Word word) {
        return c - word.c;
    }
}

import java.util.ArrayList;
 
public class List extends ArrayList<Word> {
    public Word get(char c){
        for(Word w :this){
            if(w.c == c) return w;
        }
        return null;
    }
 
    /**
     * 二分查找，必须先升序排序
     * @param c 需要查找的字符
     * @return Word对象：如果找到   null:如果没找到
     */
    public Word binaryGet(char c){
        int left,right,key;
        Word word;
        left = 0;right = this.size()-1;
        while (left <= right){
            key = (left + right) / 2;
            word = get(key);
            if(word.c == c){
                return word;
            }else if(word.c > c){
                right = key - 1;
            }else {
                left = key + 1;
            }
        }
        return null;
    }
 
    public Word add(char c){
        Word word = new Word(c);
        super.add(word);
        return word;
    }
}

import java.io.*;
import java.util.ArrayList;
import java.util.Collections;
 
 
public final class SensitiveWordFilter {
    public static List wordList;
    private final static char replace = '*'; // 替代字符
    private final static char[] skip = new char[]{ // 遇到这些字符就会跳过，例如,如果"AB"是敏感词，那么"A B","A=B"也会被屏蔽
            '!','*','-','+','_','=',',','.','@'
    };
 
    /**
     * 敏感词替换
     * @param text 待替换文本
     * @return 替换后的文本
     */
    public static String Filter(String text){
        if(wordList == null || wordList.size() == 0) return text;
        char[] __char__ = text.toCharArray(); // 把String转化成char数组，便于遍历
        int i,j;
        Word word;
        boolean flag; // 是否需要替换
        for(i=0;i<__char__.length;i++){ // 遍历所有字符
            char c = __char__[i];
            word = wordList.binaryGet(c); // 使用二分查找来寻找字符，提高效率
            if(word != null){ // word != null说明找到了
                flag = false;
                j = i+1;
                while (j < __char__.length){ // 开始逐个比较后面的字符
                    if(skip(__char__[j])) { // 跳过空格之类的无关字符
                        j++;
                        continue;
                    }
                    if(word.next != null){ // 字符串尚未结束，不确定是否存在敏感词
                        /*
                        以下代码并没有使用二分查找，因为以同一个字符开头的敏感词较少
                        例如，wordList中记录了所有敏感词的开头第一个字，它的数量通常会有上千个
                        假如现在锁定了字符“T”开头的敏感词，而“T”开头的敏感词只有10个，这时使用二分查找的效率反而低于顺序查找
                         */
                        word = word.next.get(__char__[j]);
                        if(word == null){
                            break;
                        }
                        j++;
                    }else { // 字符串已结束，存在敏感词汇
                        flag = true;
                        break;
                    }
                }
                if(word != null && word.next == null){
                    flag = true;
                }
                if(flag){ // 如果flag==true，说明检测出敏感粗，需要替换
                    while (i<j){
                        if(skip(__char__[i])){ // 跳过空格之类的无关字符，如果要把空格也替换成'*'，则删除这个if语句
                            i++;
                            continue;
                        }
                        __char__[i] = replace;
                        i++;
                    }
                    i--;
                }
            }
        }
        return new String(__char__);
    }
 
    /**
     * 加载敏感词列表
     * @param words 敏感词数组
     */
    public static void loadWord(ArrayList<String> words){
        if(words == null) return;
        char[] chars;
        List now;
        Word word;
        wordList = new List();
        for(String __word__:words){
            if(__word__ == null) continue;
            chars = __word__.toCharArray();
            now = wordList;
            word = null;
            for(char c:chars){
                if(word != null) {
                    if(word.next == null) word.next = new List();
                    now = word.next;
                }
                word = now.get(c);
                if(word == null) word = now.add(c);
            }
        }
        sort(wordList);
    }
 
    /**
     * 加载敏感词txt文件，每个敏感词独占一行，不可出现空格，空行，逗号等非文字内容,必须使用UTF-8编码
     * @param path txt文件的绝对地址
     */
    public static void loadWordFromFile(String path){
        String encoding = "UTF-8";
        File file = new File(path);
        try{
            if(file.isFile() && file.exists()){
                InputStreamReader inputStreamReader = new InputStreamReader(
                        new FileInputStream(file),encoding
                );
                BufferedReader bufferedReader = new BufferedReader(inputStreamReader);
                String line;
                ArrayList<String> list = new ArrayList<>();
                while ((line = bufferedReader.readLine()) != null){
                    list.add(line);
                }
                bufferedReader.close();
                inputStreamReader.close();
                loadWord(list);
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
 
    /**
     * 对敏感词多叉树递增排序
     * @param list 待排序List
     */
    private static void sort(List list){
        if(list == null) return;
        Collections.sort(list); // 递增排序
        for(Word word:list){
            sort(word.next);
        }
    }
 
    /**
     * 判断是否跳过当前字符
     * @param c 待检测字符
     * @return true:需要跳过   false:不需要跳过
     */
    private static boolean skip(char c){
        for(char c1:skip){
            if(c1 == c) return true;
        }
        return false;
    }
}

public class Main {
    public static void main(String[] args) throws Exception{
        SensitiveWordFilter.loadWordFromFile("D:/SensitiveWordList.txt");
        StringBuilder stringBuilder = new StringBuilder();
        long t1,t2;
        for(int i=0;i<100;i++){
            stringBuilder.append("123TM,D123");
        }
        String s = stringBuilder.toString();
        String result = null;
        t1 = System.nanoTime();
        for(int i=0;i<10000;i++){
            result = SensitiveWordFilter.Filter(s);
        }
        t2 = System.nanoTime();
        System.out.println(result);
        System.out.println((t2 - t1) / 1000000 + "毫秒");
    }
}