基于java实现DFA算法代码实例
作者:NopSmile
这篇文章主要介绍了基于java实现DFA算法代码实例,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
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<Keywords> sensitiveWords) { try { // 从敏感词集合对象中取出敏感词并封装到Set集合中 Set<String> keyWordSet = new HashSet<String>(); 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<String> keyWordSet) { // 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<String, String> newWorMap = null; // 使用一个迭代器来循环敏感词集合 Iterator<String> iterator = keyWordSet.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<String, String>(); 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; /** * 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<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); 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<String> set = getSensitiveWord(txt, matchType); 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; } /** * 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<String,Integer> map = new HashMap<String,Integer>(); 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 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<String, Integer> sortByValue(Map<String, Integer> unsortMap,int condition,boolean isCondition) { // 1. Convert Map to List of Map List<Map.Entry<String, Integer>> list = new LinkedList<Map.Entry<String, Integer>>(unsortMap.entrySet()); // 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<Map.Entry<String, Integer>>() { public int compare(Map.Entry<String, Integer> o1, Map.Entry<String, Integer> o2) { return (o2.getValue()).compareTo(o1.getValue()); } }); // 3. Loop the sorted list and put it into a new insertion order Map LinkedHashMap Map<String, Integer> sortedMap = new LinkedHashMap<String, Integer>(); if(isCondition) { for (int i = 0; i < list.size(); 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 list = 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) ;
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持脚本之家。