Package org.carrot2.text.util

Examples of org.carrot2.text.util.MutableCharArray

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       */
    case ARABIC:
      // Intentional fall-through.

    default:
      return new ExtendedWhitespaceTokenizer();
    }
  }
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    static ITokenizer createTokenizer() {
      try {
        return new ChineseTokenizer();
      } catch (Throwable e) {
        return new ExtendedWhitespaceTokenizer();
      }
    }
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    }
    return solrStopWords.get(fieldName);
  }

  public ILexicalData getLexicalData(LanguageCode languageCode) {
    final ILexicalData carrot2LexicalData = carrot2LexicalDataFactory
        .getLexicalData(languageCode);

    return new ILexicalData() {
      public boolean isStopLabel(CharSequence word) {
        // Nothing in Solr maps to the concept of a stop label,
        // so return Carrot2's default here.
        return carrot2LexicalData.isStopLabel(word);
      }

      public boolean isCommonWord(MutableCharArray word) {
        // Loop over the fields involved in clustering first
        for (String fieldName : fieldNames) {
          for (CharArraySet stopWords : getSolrStopWordsForField(fieldName)) {
            if (stopWords.contains(word)) {
              return true;
            }
          }
        }
        // Check default Carrot2 stop words too
        return carrot2LexicalData.isCommonWord(word);
      }
    };
  }
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      return;
    }

    // Test with Maltese so that the English clustering performed in other tests
    // is not affected by the test stopwords and stoplabels.
    ILexicalData lexicalData = preprocessing.lexicalDataFactory
        .getLexicalData(LanguageCode.MALTESE);

    for (String word : wordsToCheck.split(",")) {
      if (!lexicalData.isCommonWord(new MutableCharArray(word))
          && !lexicalData.isStopLabel(word)) {
        clusters.add(new Cluster(word));
      }
    }
  }
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     * one <code>language</code>.
     */
    private void cluster(LanguageCode language)
    {
        // Preprocessing of documents
        final PreprocessingContext context = preprocessingPipeline.preprocess(documents,
            query, language);

        // Further processing only if there are words to process
        clusters = Lists.newArrayList();
        if (context.hasLabels())
        {
            // Term-document matrix building and reduction
            final VectorSpaceModelContext vsmContext = new VectorSpaceModelContext(
                context);
            final ReducedVectorSpaceModelContext reducedVsmContext = new ReducedVectorSpaceModelContext(
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      private final MutableCharArray tempCharSequence;
      private final Class<?> tokenFilterClass;

      private ChineseTokenizer() throws Exception {
        this.tempCharSequence = new MutableCharArray(new char[0]);

        // As Smart Chinese is not available during compile time,
        // we need to resort to reflection.
        final Class<?> tokenizerClass = ReflectionUtils.classForName(
            "org.apache.lucene.analysis.cn.smart.SentenceTokenizer", false);
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    // is not affected by the test stopwords and stoplabels.
    ILexicalData lexicalData = preprocessing.lexicalDataFactory
        .getLexicalData(LanguageCode.MALTESE);

    for (String word : wordsToCheck.split(",")) {
      if (!lexicalData.isCommonWord(new MutableCharArray(word))
          && !lexicalData.isStopLabel(word)) {
        clusters.add(new Cluster(word));
      }
    }
  }
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    public void mark(PreprocessingContext context)
    {
        final char [][] wordImages = context.allWords.image;
        final short [] types = context.allWords.type;

        final MutableCharArray mutableCharArray = new MutableCharArray("");
        char [] buffer = new char [128];
        final ILexicalData lexData = context.language.getLexicalData();

        for (int i = 0; i < wordImages.length; i++)
        {
            final char [] word = wordImages[i];
            if (buffer.length < word.length) buffer = new char [word.length];

            CharArrayUtils.toLowerCase(word, buffer);
            mutableCharArray.reset(buffer, 0, word.length);
            if (lexData.isCommonWord(mutableCharArray))
            {
                types[i] |= ITokenizer.TF_COMMON_WORD;
            }
        }
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        for (String entry : input)
        {
            char [] chars = entry.toCharArray();
            CharArrayUtils.toLowerCaseInPlace(chars);
            cloned.add(new MutableCharArray(chars));
        }

        return cloned;
    }
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        int newLen = normalizer.normalize(buffer, word.length());
        newLen = delegate.stem(buffer, newLen);

        if (newLen != word.length() || !equals(buffer, newLen, word))
        {
            return new MutableCharArray(Arrays.copyOf(buffer, newLen));
        }

        // Same-same.
        return null;
    }
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