如何在Java项目中利用DFA算法实现一个过滤敏感字功能

这期内容当中小编将会给大家带来有关如何在Java项目中利用DFA算法实现一个过滤敏感字功能，文章内容丰富且以专业的角度为大家分析和叙述，阅读完这篇文章希望大家可以有所收获。

模式图

直接上代码

public class KeyWordFilter {//  private static ReentrantReadWriteLock lock = new ReentrantReadWriteLock();  public static Map<String, HashMap> currentMap = new ConcurrentHashMap<String, HashMap>();  public static Map nowhash = null;  public static Object wordMap;// map子节点  // 不建立对象  private KeywordFilter() {  }  private static String geTKEy(int companyId) {    return "companyId" + companyId;  }    public static void clear() {    try {      currentMap.clear();    } catch (Exception e) {      e.printStackTrace();    } finally {    }  }    public static void saveKeywords(int companyId, List<String> keywords) {    try {      Map tempAllMap = currentMap;      String key = getKey(companyId);      int l = keywords.size();      int il;      Map tempMap;      for (int i = 0; i < l; i++) {        String key2 = keywords.get(i).trim();// 去掉空白        nowhash = currentMap;        il = key2.length();        for (int j = 0; j < il; j++) {          char word = key2.charAt(j);          tempMap = (Map) nowhash.get(word);          wordMap = nowhash.get(word);          if (wordMap != null) {// 检查数据            if (!tempMap.containsKey(key)) {              nowhash.put(key, 0);            }            nowhash = (HashMap) wordMap;          } else {            HashMap<String, String> newWordHash = new HashMap<String, String>();            newWordHash.put(key, "0");            nowhash.put(word, newWordHash);            nowhash = newWordHash;          }          if (j == il - 1) {            nowhash.put(key, "1");          }        }      }    } catch (Exception e) {      e.printStackTrace();    } finally {      nowhash = null;      wordMap = null;    }  }    public static List<String> repword(int companyId, String txt) {    Map tempMap = currentMap;    List<String> result = new ArrayList<String>();    String key = getKey(companyId);    nowhash = currentMap;    int l = txt.length();    char word;    String keywordStr = "";    String keyStatu;    StringBuilder keyword = new StringBuilder();// 敏感字    for (int i = 0; i < l; i++) {      word = txt.charAt(i);      wordMap = nowhash.get(word);      if (wordMap != null) {// 找到类似敏感字的字体，开始查询        keyword.append(word);        Object te = nowhash = (HashMap) wordMap;        // 遍历到这一步，就符合完整的关键字模板        if (nowhash.get(key) != null            && nowhash.get(key).toString().equals("1")) {// 确定是敏感字，开始替换          if (i < l - 1 && nowhash.get(txt.charAt(i + 1)) != null) {// 优先过滤长敏感词，去掉就槟城了优先过滤段敏感词            continue;          }          txt = txt.replaceAll(keyword.toString(), "*");          nowhash = currentMap;          keywordStr += keyword.toString() + ",";          i = i - keyword.length() + 1;          l = txt.length();// 重新获取字符长度          keyword.delete(0, keyword.length());// 清空数据        }      } else {// 这个字不是敏感字，直接排除        nowhash = currentMap;        keyword.delete(0, keyword.length());// 清空数据        continue;      }    }    // 清除内存指向    nowhash = null;    wordMap = null;    result.add(txt);    result.add(keywordStr.length() - 1 > 0 &#63; keywordStr.substring(0,        keywordStr.length() - 1) : keywordStr);    return result;  }    private static int checkKeyWords(String txt, int companyId, int begin) {    int result = 0;    String key = getKey(companyId);    try {      nowhash = currentMap;      int l = txt.length();      char word = 0;      for (int i = begin; i < l; i++) {        word = txt.charAt(i);        wordMap = nowhash.get(word);        if (wordMap != null) {          result++;          nowhash = (HashMap) wordMap;          if (((String) nowhash.get(key)).equals("1")) {            nowhash = null;            wordMap = null;            return result;          }        } else {          result = 0;          break;        }      }    } catch (Exception e) {      e.printStackTrace();    } finally {      nowhash = null;      wordMap = null;      return result;    }  }    public static String getTxtKeyWords(String txt, int companyId) {    String result = null;    StringBuilder temp = new StringBuilder();    String key;    int l = txt.length();    for (int i = 0; i < l;) {      int len = checkKeyWords(txt, companyId, i);      if (len > 0) {        key = (txt.substring(i, i + len));// 挑选出来的关键字        temp.append(key + ",");        txt = txt.replaceAll(key, "");// 挑选出来的关键字替换成空白，加快挑选速度        l = txt.length();      } else {        i++;      }    }    if (temp.length() > 0) {      result = temp.substring(0, temp.length() - 1);    }    return result;  }    public boolean isKeyWords(String txt, int companyId) {    for (int i = 0; i < txt.length(); i++) {      int len = checkKeyWords(txt, companyId, i);      if (len > 0) {        return true;      }    }    return false;  }  public static void main(String[] arg) {    List<String> keywords = new ArrayList<String>();    keywords.add("傻×");    keywords.add("汉*");    keywords.add("草");    keywords.add("草泥马");    KeywordFilter.saveKeywords(1, keywords);    String txt = "是傻×汉*傻A傻B傻C傻D汉*傻×草泥马";    List<String> list = repword(1, txt);    System.out.println("文中包含的敏感字为:" + list.get(1));    System.out.println("原文:" + txt);    System.out.println("敏感字过滤后:" + list.get(0));  }}