Trie树的简单应用

简单语法匹配

import java.util.ArrayList;import java.util.HashSet;import java.util.LinkedList;import java.util.List;import java.util.Queue;import java.util.Set;public class SemanticTrie {/***a adjective 美丽 ni organization name 保险公司*b other noun-modifier 大型, 西式 nl location noun 城郊*c conjunction 和, 虽然 ns geographical name 北京*d adverb 很 nt temporal noun 近日, 明代*e exclamation 哎 nz other proper noun 诺贝尔奖*g morpheme 茨, 甥 o onomatopoeia 哗啦*h prefix 阿, 伪 p preposition 在, 把*i idiom 百花齐放 q quantity 个*j abbreviation 公检法 r pronoun 我们*k suffix 界, 率 u auxiliary 的, 地*m number 一, 第一 v verb 跑, 学习*n general noun 苹果 wp punctuation ，。！*nd direction noun 右侧 ws foreign words CPU*nh person name 杜甫, 汤姆 x non-lexeme 萄, 翱   **/public static final String [] tags={"a","b","c","d","e","f","g","h","i","j","k","m","n","nd","nh","ni","nl","ns","nt","nz","o","p","q","r","u","v","wp","ws","x"};public static SemanticTrie semanticTrie=new SemanticTrie();static{System.out.println("初始化语法");semanticTrie.addVertex("a+b+c");semanticTrie.addVertex("k+b+c+a");semanticTrie.addVertex("a+nh+c+o");semanticTrie.addVertex("nz+p+wp+a+c+d");System.out.println("初始化结束");}/** * 获得单个词性的索引 * @param tag * @return */public  int getTagIndex(String tag){if (tag==null||tag.isEmpty()) {return -1;}for (int i = 0; i < tags.length; i++) {if (tag.toLowerCase().equals(tags[i])) {return i;}}return -1;}/** * 一个Trie树有一个根节点 */public Vertex root;/** * 节点内部类 */protected class Vertex {/** * 词性 */protected String tag;/** * 是否是完整的语法 */protected boolean isFull;/** * 前缀出现次数 */protected int count;protected Vertex[] edges;// 每个节点包含29个子节点(类型为自身)Vertex() {tag="";isFull=false;count = 0;edges = new Vertex[tags.length];for (int i = 0; i < edges.length; i++) {edges[i] = null;}}}public SemanticTrie(){root=new Vertex();}/** * 添加语法 * @param grammar 语法以“+”分割 例： a+b+c */public void addVertex(String grammar){if(grammar==null||grammar.trim().isEmpty()){return;}String[]grammars=grammar.split("\\+");Queue<String> grammarQueue=new LinkedList<String>();for (String str : grammars) {if (!str.trim().isEmpty()) {grammarQueue.add(str);}}this.addVertex(root,grammarQueue);}/** * 添加语法节点 * @param vertex * @param grammarQueue */public void addVertex(Vertex vertex,Queue<String> grammarQueue){if (grammarQueue.size()<=0) {//设为是完整的语法vertex.isFull=true;}else {String tag=grammarQueue.poll();int index=this.getTagIndex(tag);if (index<0) {addVertex(vertex, grammarQueue);}else {if (vertex.edges[index]==null) {vertex.edges[index]=new Vertex();vertex.edges[index].tag=tag;}else {vertex.edges[index].tag=tag;}//出现次数vertex.count++;//调用下一个addVertex(vertex.edges[index], grammarQueue);}}}/** * 深度遍历所有存在的语法 * @param grammarList 结果list * @param vertex 节点 * @param segment 节点值片段 */private void depthFirstAll(List<String> grammarList,Vertex vertex,String segment){Vertex[] edges = vertex.edges;for (int i = 0; i < edges.length; i++) {if (edges[i] != null) {String temSeg = segment + edges[i].tag+"+";if (edges[i].isFull==true) {grammarList.add(temSeg.substring(0,temSeg.length()-1));}depthFirstAll(grammarList, edges[i], temSeg);}}}/** * 获得所有的语法 */public List<String> getAllGrammar(){List<String> grammarList=new ArrayList<String>();depthFirstAll(grammarList, root, "");return grammarList;}/** * 获得符合的语法《string》 * @param grammar * @return */public Set<String> getMatchGrammar(String grammar){if(grammar==null||grammar.trim().isEmpty()){return null;}String[]grammars=grammar.split("\\+");Queue<String> grammarQueue=new LinkedList<String>();for (String str : grammars) {if (!str.trim().isEmpty()) {grammarQueue.add(str);}}Set<String> grammarList=new HashSet<String>();selectMatchGrammar(grammarList, root, grammarQueue, "");return grammarList;}/** * 搜索符合的语法《string》 * @param grammarList 结果列表 * @param vertex 开始节点 * @param tempQuery 词性队列 */public void selectMatchGrammar(Set<String> grammarList,Vertex vertex,Queue<String> tempQuery,String segment){if (tempQuery==null||tempQuery.size()<=0) {return ;}System.out.println(tempQuery.toString());while (tempQuery.size()>0) {String tag=tempQuery.poll();int index=this.getTagIndex(tag);if (index<0) {continue;}if (vertex.edges[index]==null) {continue;}Vertex temV=vertex.edges[index];//语法String temSeg=segment+tag+"+";if (temV.isFull==true) {grammarList.add(temSeg.substring(0,temSeg.length()-1));}Queue<String> temQ=copy(tempQuery);selectMatchGrammar(grammarList,temV,temQ,temSeg);}}/** * 复制对象《string》 * @param fromQueue * @param toQueue */public Queue<String> copy(Queue<String> fromQueue){try {if (fromQueue==null) {return null;}Queue<String>  toQueue=new LinkedList<String>();Object[] array=fromQueue.toArray();for (Object object : array) {toQueue.add((String)object);}return toQueue;} catch (Exception e) {e.printStackTrace();return null;}}public static void main(String[] args) {List<String> grammarLista=SemanticTrie.semanticTrie.getAllGrammar();for (String string : grammarLista) {System.out.println(string);}System.out.println("-----------------------");Set<String> grammarList=SemanticTrie.semanticTrie.getMatchGrammar("a+b+nh+c+h+o+a+wp+d+b");for (String string : grammarList) {System.out.println(string);}}}