关于lucene的分词(三)

到此为止这个简单的但是功能强大的分词器就写完了,下面咱们可以尝试写一个功能更强大的分词器.

如何DIY一个功能更加强大Analyzer

譬如你有词典,然后你根据正向最大匹配法或者逆向最大匹配法写了一个分词方法,却想在Lucene中应用,很简单

你只要把他们包装成LuceneTokenStream就好了.下边我以调用中科院写的ICTCLAS接口为例,进行演示.你去中科院

网站可以拿到此接口的free版本,谁叫你没钱呢,有钱,你就可以购买了.哈哈

,由于ICTCLAS进行分词之后,Java,中间会以两个空格隔开!too easy,我们直接使用继承Lucene

WhiteSpaceTokenizer就好了.

所以TjuChineseTokenizer 看起来像是这样.

public class TjuChineseTokenizer extends WhitespaceTokenizer

{

public TjuChineseTokenizer(Reader readerInput)

{

    super(readerInput);

}

}

TjuChineseAnalyzer看起来象是这样

public final class TjuChineseAnalyzer

    extends Analyzer

{

private Set stopWords;

 

/** An array containing some common English words that are not usually useful

    for searching. */

/*

     public static final String[] CHINESE_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",

      "", "我们"

     };

   */

/** Builds an analyzer which removes words in ENGLISH_STOP_WORDS. */

public TjuChineseAnalyzer()

{

    stopWords = StopFilter.makeStopSet(StopWords.SMART_CHINESE_ENGLISH_STOP_WORDS);

}

 

/** Builds an analyzer which removes words in the provided array. */

//提供独自的stopwords

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);

      //分词中间加入了空格

      String resultString = splitWord.paragraphProcess(inputString);

      System.out.println(resultString);

      TokenStream result = new TjuChineseTokenizer(new StringReader(resultString));

 

      result = new LowerCaseFilter(result);

      //使用stopWords进行过滤

     result = new StopFilter(result, stopWords);

      //使用p-stemming算法进行过滤

     result = new PorterStemFilter(result);

      return result;

 

    }

    catch (IOException e)

    {

      System.out.println("转换出错");

      return null;

    }

}

 

public static void main(String[] args)

{

    String string = "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();

    }

}

}


对于此程序的输出接口可以看一下

0->Token's (termText,startOffset,endOffset,type,positionIncrement) is:(,3,4,word,1)

1->Token's (termText,startOffset,endOffset,type,positionIncrement) is:(中国,6,8,word,1)

2->Token's (termText,startOffset,endOffset,type,positionIncrement) is:(人民,10,12,word,1)

 

OK,经过这样一番讲解,你已经对LuceneAnalysis包认识的比较好了,当然如果你想更加了解,还是认真读读源码才好,

呵呵,源码说明一切!

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