Lucene源代码之构造自己的分词器

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package org.apache.lucene.analysis.tjuchinese;
import java.io.IOException;
import java.io.Reader;
import java.io.StringReader;
import java.util.Set;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.StopFilter;
import org.apache.lucene.analysis.TokenStream;
import com.xjt.nlp.word.ICTCLAS;
public final class TjuChineseAnalyzer extends Analyzer {
private Set stopWords;
// 可以在此扩展English stop words和Chinese stop words
public static final String[] ENGLISH_STOP_WORDS = { "a", "an", "and",
"are", "as", "at", "be", "but", "by", "for", "if", "in", "into",
"is", "it", "no", "not", "of", "on", "or", "s", "such", "t",
"that", "the", "their", "then", "there", "these", "they", "this",
"to", "was", "will", "with", "我", "我们" };
/** Builds an analyzer which removes words in ENGLISH_STOP_WORDS. */
public TjuChineseAnalyzer() {
stopWords = StopFilter.makeStopSet(ENGLISH_STOP_WORDS);
}
/** Builds an analyzer which removes words in the provided array. */
public TjuChineseAnalyzer(String[] stopWords) {
this.stopWords = StopFilter.makeStopSet(stopWords);
}
/** Filters LowerCaseTokenizer with StopFilter. */
public TokenStream tokenStream(String fieldName, Reader reader) {
try {
ICTCLAS splitWord = new ICTCLAS();
String inputString = FileIO.readerToString(reader);
String resultString = splitWord.paragraphProcess(inputString);
TokenStream result = new TjuChineseTokenizer(new StringReader(
resultString));
result = new StopFilter(result, stopWords);
return result;
/*
* return new StopFilter(new LowerCaseTokenizer(new StringReader(
* resultString)), stopWords);
*/
} catch (IOException e) {
System.out.println("转换出错");
return null;
}
}
}

TjuChineseTokenizer.java;

package org.apache.lucene.analysis.tjuchinese;
import java.io.Reader;
import org.apache.lucene.analysis.LowerCaseTokenizer;
public class TjuChineseTokenizer extends LowerCaseTokenizer{
public TjuChineseTokenizer(Reader Input)
{
super(Input);
}
}

FileIO.java;

package org.apache.lucene.analysis.tjuchinese;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.Reader;
public class FileIO {
public static String readerToString(Reader reader) throws IOException {
BufferedReader br = new BufferedReader(reader);
String ttt = null;
// 使用 StringBuffer 类，可以提高字符串操作的效率
StringBuffer tttt = new StringBuffer("");
while ((ttt = br.readLine()) != null) {
tttt.append(ttt);
}
return tttt.toString();
}
}

eclipse里面的部署为：

搞定！！

下面测试一下，测试代码如下：

package org.apache.lucene.analysis.tjuchinese;
import java.io.IOException;
import java.io.StringReader;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.Token;
import org.apache.lucene.analysis.TokenStream;
public class testTjuChjnese {
public static void main(String[] args) {
String string = "hello!我爱中国人民";
Analyzer analyzer = new TjuChineseAnalyzer();
TokenStream ts = analyzer
.tokenStream("dummy", new StringReader(string));
Token token;
System.out.println("Tokens:");
try {
int n = 0;
while ((token = ts.next()) != null) {
System.out.println((n++) + "->" + token.toString());
}
} catch (IOException ioe) {
ioe.printStackTrace();
}
}
}

运行结果：

Tokens:
0->(hello,0,5)
1->(nx,6,8)
2->(w,12,13)
3->(r,17,18)
4->(爱,20,21)
5->(v,22,23)
6->(中国,25,27)
7->(ns,28,30)
8->(人民,32,34)
9->(n,35,36)

【难点】

public CharArraySet(int startSize, boolean ignoreCase) {
this.ignoreCase = ignoreCase;
int size = INIT_SIZE;
while(startSize + (startSize>>2) > size)
size <<= 1;
entries = new char[size][];
}

startSize + (startSize>>2，不解？

附录：

因为本分词器要用到ICTCLAS java接口。所以要先下载下载地址http://download.csdn.net/source/778456；

将文件全部复制到工程文件中（也可以通过导入）后，得到的eclipse视图如下：

导入视图如下（仅供参考）：

如果出现这样的错误：

java.lang.UnsatisfiedLinkError: no ICTCLAS in java.library.path
at java.lang.ClassLoader.loadLibrary(Unknown Source)
at java.lang.Runtime.loadLibrary0(Unknown Source)
at java.lang.System.loadLibrary(Unknown Source)
at com.xjt.nlp.word.ICTCLAS.<clinit>(ICTCLAS.java:37)
Exception in thread "main"
那么应该就是你缺少了某些文件，尤其是ICTCLAS.dll，另外像“classes”、“data”、“lib”源文件夹也是必需的。