lucene3 中文IKAnalyzer分词例子

import java.io.IOException;
import java.io.StringReader;
import java.util.Iterator;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;
import org.apache.lucene.util.AttributeImpl;
import org.wltea.analyzer.lucene.IKAnalyzer;
import org.wltea.analyzer.lucene.IKQueryParser;
import org.wltea.analyzer.lucene.IKSimilarity;
/**
 * 采用IKAanlyzer分词器查询
 * @author admin
 *
 */
public class IKAnalyzerSearchWord {
    private static String fieldName = "text";
    public  static void searchWord(String field ,String keyword) {
        if(null!=field&&!"".equals(field)){
            fieldName = field;
        }
        String text = "IK Analyzer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。从2006年12月推出1.0版开始， " +
                "IKAnalyzer已经推出了3个大版本。最初，它是以开源项目Luence为应用主体的，结合词典分词和文法分析算法的中文分词组件。" +
                "新版本的IK Analyzer 3.0则发展为面向Java的公用分词组件，独立于Lucene项目，同时提供了对Lucene的默认优化实现。 ";
        Analyzer analyzer = new IKAnalyzer();
        StringReader reader = new StringReader(text);

        long startTime = System.currentTimeMillis();    //开始时间
        TokenStream ts = analyzer.tokenStream("*", reader);
        Iterator<AttributeImpl> it = ts.getAttributeImplsIterator();
        while(it.hasNext()){
            System.out.println((AttributeImpl)it.next());
        }
        System.out.println("");

        long endTime = System.currentTimeMillis();  //结束时间
        System.out.println("IK分词耗时" + new Float((endTime - startTime)) / 1000 + "秒!");
        Directory dir = null;
        IndexWriter writer = null;
        IndexSearcher searcher = null;
        try {
            dir = new RAMDirectory();
            writer = new IndexWriter(dir, analyzer, true,
                    IndexWriter.MaxFieldLength.LIMITED);
            System.out.println(IndexWriter.MaxFieldLength.LIMITED);
            Document doc = new Document();
            doc.add(new Field(fieldName, text, Field.Store.YES,
                    Field.Index.ANALYZED));
            writer.addDocument(doc);
            writer.close();
            //在索引其中使用IKSimilarity相似评估度
            searcher = new IndexSearcher(dir);
            searcher.setSimilarity(new IKSimilarity());
            Query query = IKQueryParser.parse(fieldName, keyword);
            TopDocs topDocs = searcher.search(query, 5);
            System.out.println("命中："+topDocs.totalHits);
            ScoreDoc[] scoreDocs = topDocs.scoreDocs;
            for (int i = 0; i < scoreDocs.length; i++) {
                Document targetDoc = searcher.doc(scoreDocs[i].doc);
                System.out.println("內容："+targetDoc.toString());
            }
        } catch (Exception e) {
            System.out.println(e);
        }finally{
            try {
                searcher.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
            try {
                dir.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }
    public static void main(String[] args) {
        long a = System.currentTimeMillis();
        IKAnalyzerSearchWord.searchWord("","中文分词工具包");
        System.out.println(System.currentTimeMillis()-a);
    }
}