Lucene使用IK中文分词

环境

• Lucene 6.x
• IKAnalyzer2012_u6

也可以通过Maven或Gradle构建工程测试和验证
对于Lucene的最新版本，需要找到IK Analyzer对应的兼容版。

传送门 Lucene 6.6.6 Documentation

IK中文分词配置

Lucene 6.x使用IK分词需要继承Analyzer、Tokenizer，重新编写逻辑配置，再使用。分别配置子类IKAnalyzer6x、IKTokenizer6x

IKAnalyzer6x.java

package com.liuyu.lucene.ik;

import org.apache.lucene.analysis.Tokenizer;
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;
import org.apache.lucene.analysis.tokenattributes.OffsetAttribute;
import org.apache.lucene.analysis.tokenattributes.TypeAttribute;
import org.wltea.analyzer.core.IKSegmenter;
import org.wltea.analyzer.core.Lexeme;

import java.io.IOException;

/**
 * @author huangliuyu
 * @description
 * @date 2021-04-21
 */
public class IKTokenizer6x extends Tokenizer {
    //IK分词器实现
    private IKSegmenter _IKImplement;
    //词元文本属性
    private final CharTermAttribute termAtt;
    //词元位移属性
    private final OffsetAttribute offsetAtt;
    //词分类属性
    //（该属性分类参考org.wltea.analyzer.core.Lexeme中的分类常量）
    private final TypeAttribute typeAtt;
    //记录最后一个词元的结束位置
    private int endPosition;

    //Lucene 6.x Tokenizer适配器类构造函数：实现Tokenizer接口
    public IKTokenizer6x(boolean useSmart) {
        super();
        offsetAtt=super.addAttribute(OffsetAttribute.class);
        termAtt=super.addAttribute(CharTermAttribute.class);
        typeAtt=super.addAttribute(TypeAttribute.class);
        _IKImplement=new IKSegmenter(input,useSmart);
    }


    public boolean incrementToken() throws IOException {
        //清除所有的词元属性
        super.clearAttributes();
        Lexeme nextLexeme=_IKImplement.next();
        if(null!=nextLexeme){
            //将Lexeme转成Attribute

            //设置词元文本
            termAtt.append(nextLexeme.getLexemeText());
            //设置词元长度
            termAtt.setLength(nextLexeme.getLength());
            //设置词元位移
            offsetAtt.setOffset(nextLexeme.getBeginPosition(),nextLexeme.getEndPosition());
            //记录分词的最后位置
            endPosition=nextLexeme.getEndPosition();
            //记录词元分类
            typeAtt.setType(nextLexeme.getLexemeText());
            //返回true告知还有下个词元
            return true;

        }
        //返回false告知词元输出完毕
        return false;
    }

    @Override
    public void reset() throws IOException {
        super.reset();
        _IKImplement.reset(input);
    }

    @Override
    public void end() throws IOException {
        int finalOffset=super.correctOffset(this.endPosition);
        offsetAtt.setOffset(finalOffset,finalOffset);
    }
}

IKAnalyzer6x.java

package com.liuyu.lucene.ik;


import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.Tokenizer;

/**
 * @author huangliuyu
 * @date 2021-04-21
 * @description
 */
public class IKAnalyzer6x extends Analyzer {
    private boolean useSmart;

    public void setUseSmart(boolean useSmart) {
        this.useSmart = useSmart;
    }

    /**
     *  IK分词器Lucene Analyzer接口实现类
     *  默认细粒度切分算法
     */
    public IKAnalyzer6x(){
        this(false);
    }

    /**
     *  IK分词器Lucene Analyzer接口实现类
     *  当为true时，分词器进行智能切分
     * @param useSmart
     */
    public IKAnalyzer6x(boolean useSmart) {
        super();
        this.useSmart=useSmart;
    }

    @Override
    protected TokenStreamComponents createComponents(String fieldName) {
    	//使用配置好的ik Tokenizer
        Tokenizer _IKTokenizer=new IKTokenizer6x(this.useSmart);
        return new TokenStreamComponents(_IKTokenizer);
    }

}

使用和比较

这里使用 Lucene 6.X自带的中文智能分词器 SmartChineseAnalyzer与IK Analyzer作比较，演示使用情况

代码

package com.liuyu.lucene.ik;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.cn.smart.SmartChineseAnalyzer;
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;

import java.io.IOException;
import java.io.StringReader;

/**
 * @author huangliuyu
 * @date 2021-04-21
 * @description
 */
public class IkVSSmartCn {
    private static String str1 = "公路局正在治理解放大道路面积水问题。";
    private static String str2 = "IKAnalyzer是一个开源的，基于java语言开发的轻量级的中文分词工具包。";

    public static void main(String[] args) throws IOException {
        Analyzer analyzer = null;

        System.out.println("句子一：" + str1);

        System.out.println("SmartChineseAnalyzer分词结果：");
        analyzer = new SmartChineseAnalyzer();
        printAnalyzer(analyzer, str1);

        System.out.println("IKAnalyzer分词结果：");
        analyzer = new IKAnalyzer6x(true);
        printAnalyzer(analyzer, str1);

        System.out.println();
        System.out.println("-------------------------------------------------");
        System.out.println();

        System.out.println("句子二：" + str2);

        System.out.println("SmartChineseAnalyzer分词结果：");
        analyzer = new SmartChineseAnalyzer();
        printAnalyzer(analyzer, str2);

        System.out.println("IKAnalyzer分词结果：");
        analyzer = new IKAnalyzer6x(true);
        printAnalyzer(analyzer, str2);

    }


    public static void printAnalyzer(Analyzer analyzer, String str) throws IOException {
        StringReader reader = new StringReader(str);
        TokenStream toStream = analyzer.tokenStream(str, reader);
        toStream.reset();//清空流

        CharTermAttribute teAttribute = toStream.getAttribute(CharTermAttribute.class);

        while (toStream.incrementToken()) {
            System.out.print(teAttribute.toString() + "|");
        }
        System.out.println("\n");
        analyzer.close();
    }

}

效果

由效果可见IK Analyzer的中文分词效果要比Lucene SmartChineseAnalyzer的好。