java实现中文分词

IK Analyzer是基于lucene实现的分词开源框架

下载路径:http://so.youkuaiyun.com/so/search/s.do?q=IKAnalyzer2012.jar&t=doc&o=&s=all&l=null

需要在项目中引入:

  IKAnalyzer2012.jar

  lucene-core-3.6.0.jar

实现的两种方法:

使用(lucene)实现:

 1 import java.io.IOException;
 2 import java.io.StringReader;
 3 import org.wltea.analyzer.core.IKSegmenter;
 4 import org.wltea.analyzer.core.Lexeme;
 5 
 6 public class Fenci1 {
 7     public static void main(String[] args) throws IOException{
 8         String text="你好,我的世界!";  
 9         StringReader sr=new StringReader(text);  
10         IKSegmenter ik=new IKSegmenter(sr, true);  
11         Lexeme lex=null;  
12         while((lex=ik.next())!=null){  
13             System.out.print(lex.getLexemeText()+",");  
14         } 
15     }
16 
17 }

 

使用(IK Analyzer)实现:

 1 import java.io.IOException;
 2 import java.io.StringReader;
 3 import org.apache.lucene.analysis.Analyzer;
 4 import org.apache.lucene.analysis.TokenStream;
 5 import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;
 6 import org.wltea.analyzer.lucene.IKAnalyzer;
 7 
 8 public class Fenci {
 9     public static void main(String[] args) throws IOException {
11             String text="你好,我的世界!";  
12             //创建分词对象  
13             Analyzer anal=new IKAnalyzer(true);       
14             StringReader reader=new StringReader(text);  
15             //分词  
16             TokenStream ts=anal.tokenStream("", reader);  
17             CharTermAttribute term=ts.getAttribute(CharTermAttribute.class);  
18             //遍历分词数据  
19             while(ts.incrementToken()){  
20                 System.out.print(term.toString()+",");  
21             }  
22             reader.close();  
23             System.out.println(); 
24     }
25 
26 }

运行后结果:

你好,我,的,世界,

转载于:https://www.cnblogs.com/chenrenshui/p/7273551.html

import WordSegment.*; import java.awt.event.ActionEvent; import java.awt.event.ActionListener; import java.awt.*; import java.io.File; import java.util.Vector; import javax.swing.*; /** * */ /** * @author Truman * */ public class WordSegDemoFrame extends JFrame implements ActionListener { final static int ALGO_FMM = 1; final static int ALGO_BMM = 2; private JMenuBar menuBar = new JMenuBar(); private JMenuItem openDicItem, closeItem; private JRadioButtonMenuItem fmmItem, bmmItem; private JMenuItem openTrainFileItem, saveDicItem, aboutItem; private JButton btSeg; private JTextField tfInput; private JTextArea taOutput; private JPanel panel; JLabel infoDic, infoAlgo; private WordSegment seger; private DicTrainer trainer = new DicTrainer(); private void initFrame() { setTitle("Mini分词器"); setDefaultCloseOperation(EXIT_ON_CLOSE); setJMenuBar(menuBar); JMenu fileMenu = new JMenu("文件"); JMenu algorithmMenu = new JMenu("分词算法"); JMenu trainMenu = new JMenu("训练语料"); JMenu helpMenu = new JMenu("帮助"); openDicItem = fileMenu.add("载入词典"); fileMenu.addSeparator(); closeItem = fileMenu.add("退出"); algorithmMenu.add(fmmItem = new JRadioButtonMenuItem("正向最大匹配", true)); algorithmMenu.add(bmmItem = new JRadioButtonMenuItem("逆向最大匹配", false)); ButtonGroup algorithms = new ButtonGroup(); algorithms.add(fmmItem); algorithms.add(bmmItem); openTrainFileItem = trainMenu.add("载入并训练语料"); saveDicItem = trainMenu.add("保存词典"); aboutItem = helpMenu.add("关于Word Segment Demo"); menuBar.add(fileMenu); menuBar.add(algorithmMenu); menuBar.add(trainMenu); menuBar.add(helpMenu); openDicItem.addActionListener(this); closeItem.addActionListener(this); openTrainFileItem.addActionListener(this); saveDicItem.addActionListener(this); aboutItem.addActionListener(this); fmmItem.addActionListener(this); bmmItem.addActionListener(this); JPanel topPanel = new JPanel(); topPanel.setLayout(new FlowLayout());
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