Package org.apache.lucene.queries.mlt

Examples of org.apache.lucene.queries.mlt.MoreLikeThis$FreqQ

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      id = Integer.parseInt(getString(docNum, "text"));
    } catch (NumberFormatException nfe) {
      errorMsg("Invalid document number");
      return;
    }
    MoreLikeThis mlt = new MoreLikeThis(ir);
    try {
      mlt.setFieldNames((String[])Util.fieldNames(ir, true).toArray(new String[0]));
    } catch (Exception e) {
      errorMsg("Exception collecting field names: " + e.toString());
      return;
    }
    mlt.setMinTermFreq(1);
    mlt.setMaxQueryTerms(50);
    Analyzer a = createAnalyzer(find("srchOptTabs"));
    if (a == null) {
      return;
    }
    mlt.setAnalyzer(a);
    Object[] rows = getSelectedItems(docTable);
    BooleanQuery similar = null;
    if (rows != null && rows.length > 0) {
      // collect text from fields
      StringBuilder sb = new StringBuilder();
      for (int i = 0; i < rows.length; i++) {
        Field f = (Field)getProperty(rows[i], "field");
        if (f == null) {
          continue;
        }
        String s = f.stringValue();
        if (s == null || s.trim().length() == 0) {
          continue;
        }
        if (sb.length() > 0) sb.append(" ");
        sb.append(s);
      }
      try {
        similar = (BooleanQuery)mlt.like("field", new StringReader(sb.toString()));
      } catch (Exception e) {
        e.printStackTrace();
        errorMsg("FAILED: " + e.getMessage());
        return;
      }
    } else {
      try {
        similar = (BooleanQuery)mlt.like(id);
      } catch (Exception e) {
        e.printStackTrace();
        errorMsg("FAILED: " + e.getMessage());
        return;
      }
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   */
  @Override
  public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer, Query query) throws IOException {
    this.textFieldNames = new String[]{textFieldName};
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(new String[]{textFieldName});
    indexSearcher = new IndexSearcher(atomicReader);
    this.query = query;
  }
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   */
  @Override
  public void train(AtomicReader atomicReader, String[] textFieldNames, String classFieldName, Analyzer analyzer, Query query) throws IOException {
    this.textFieldNames = textFieldNames;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(textFieldNames);
    indexSearcher = new IndexSearcher(atomicReader);
    this.query = query;
  }
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   */
  @Override
  public void train(AtomicReader atomicReader, String[] textFieldNames, String classFieldName, Analyzer analyzer, Query query) throws IOException {
    this.textFieldNames = textFieldNames;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(textFieldNames);
    indexSearcher = new IndexSearcher(atomicReader);
    if (minDocsFreq > 0) {
      mlt.setMinDocFreq(minDocsFreq);
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   */
  @Override
  public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer) throws IOException {
    this.textFieldName = textFieldName;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(new String[]{textFieldName});
    indexSearcher = new IndexSearcher(atomicReader);
  }
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   */
  @Override
  public void train(AtomicReader atomicReader, String[] textFieldNames, String classFieldName, Analyzer analyzer, Query query) throws IOException {
    this.textFieldNames = textFieldNames;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(textFieldNames);
    indexSearcher = new IndexSearcher(atomicReader);
    if (minDocsFreq > 0) {
      mlt.setMinDocFreq(minDocsFreq);
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   */
  @Override
  public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer) throws IOException {
    this.textFieldName = textFieldName;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(new String[]{textFieldName});
    indexSearcher = new IndexSearcher(atomicReader);
  }
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   */
  @Override
  public void train(AtomicReader atomicReader, String[] textFieldNames, String classFieldName, Analyzer analyzer, Query query) throws IOException {
    this.textFieldNames = textFieldNames;
    this.classFieldName = classFieldName;
    mlt = new MoreLikeThis(atomicReader);
    mlt.setAnalyzer(analyzer);
    mlt.setFieldNames(textFieldNames);
    indexSearcher = new IndexSearcher(atomicReader);
    if (minDocsFreq > 0) {
      mlt.setMinDocFreq(minDocsFreq);
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*/
public class MoreLikeThisHelper {

    public static Query getMoreLikeThis(IndexReader reader, Analyzer analyzer, String mltQueryString) {
        Query moreLikeThisQuery = null;
        MoreLikeThis mlt = new MoreLikeThis(reader);
        mlt.setAnalyzer(analyzer);
        try {
            String text = null;
            String[] fields = {};
            for (String param : mltQueryString.split("&")) {
                String[] keyValuePair = param.split("=");
                if (keyValuePair.length != 2 || keyValuePair[0] == null || keyValuePair[1] == null) {
                    throw new RuntimeException("Unparsable native Lucene MLT query: " + mltQueryString);
                } else {
                    if ("stream.body".equals(keyValuePair[0])) {
                        text = keyValuePair[1];
                    } else if ("mlt.fl".equals(keyValuePair[0])) {
                        fields = keyValuePair[1].split(",");
                    } else if ("mlt.mindf".equals(keyValuePair[0])) {
                        mlt.setMinDocFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.mintf".equals(keyValuePair[0])) {
                        mlt.setMinTermFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.boost".equals(keyValuePair[0])) {
                        mlt.setBoost(Boolean.parseBoolean(keyValuePair[1]));
                    } else if ("mlt.qf".equals(keyValuePair[0])) {
                        mlt.setBoostFactor(Float.parseFloat(keyValuePair[1]));
                    } else if ("mlt.maxdf".equals(keyValuePair[0])) {
                        mlt.setMaxDocFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxdfp".equals(keyValuePair[0])) {
                        mlt.setMaxDocFreqPct(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxntp".equals(keyValuePair[0])) {
                        mlt.setMaxNumTokensParsed(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxqt".equals(keyValuePair[0])) {
                        mlt.setMaxQueryTerms(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxwl".equals(keyValuePair[0])) {
                        mlt.setMaxWordLen(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.minwl".equals(keyValuePair[0])) {
                        mlt.setMinWordLen(Integer.parseInt(keyValuePair[1]));
                    }
                }
            }
            if (text != null) {
                if (FieldNames.PATH.equals(fields[0])) {
                    IndexSearcher searcher = new IndexSearcher(reader);
                    TermQuery q = new TermQuery(new Term(FieldNames.PATH, text));
                    TopDocs top = searcher.search(q, 1);
                    if (top.totalHits == 0) {
                        mlt.setFieldNames(fields);
                        moreLikeThisQuery = mlt.like(new StringReader(text), mlt.getFieldNames()[0]);
                    } else{
                        ScoreDoc d = top.scoreDocs[0];
                        Document doc = reader.document(d.doc);
                        List<String> fieldNames = new ArrayList<String>();
                        for (IndexableField f : doc.getFields()) {
                            if (!FieldNames.PATH.equals(f.name())) {
                                fieldNames.add(f.name());
                            }
                        }
                        String[] docFields = fieldNames.toArray(new String[0]);
                        mlt.setFieldNames(docFields);
                        moreLikeThisQuery = mlt.like(d.doc);
                    }
                } else {
                    mlt.setFieldNames(fields);
                    moreLikeThisQuery = mlt.like(new StringReader(text), mlt.getFieldNames()[0]);
                }
            }
            return moreLikeThisQuery;
        } catch (Exception e) {
            throw new RuntimeException("could not handle MLT query " + mltQueryString);
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*/
public class MoreLikeThisHelper {

    public static Query getMoreLikeThis(IndexReader reader, Analyzer analyzer, String mltQueryString) {
        Query moreLikeThisQuery = null;
        MoreLikeThis mlt = new MoreLikeThis(reader);
        mlt.setAnalyzer(analyzer);
        try {
            String text = null;
            for (String param : mltQueryString.split("&")) {
                String[] keyValuePair = param.split("=");
                if (keyValuePair.length != 2 || keyValuePair[0] == null || keyValuePair[1] == null) {
                    throw new RuntimeException("Unparsable native Lucene MLT query: " + mltQueryString);
                } else {
                    if ("stream.body".equals(keyValuePair[0])) {
                        text = keyValuePair[1];
                    } else if ("mlt.fl".equals(keyValuePair[0])) {
                        mlt.setFieldNames(keyValuePair[1].split(","));
                    } else if ("mlt.mindf".equals(keyValuePair[0])) {
                        mlt.setMinDocFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.mintf".equals(keyValuePair[0])) {
                        mlt.setMinTermFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.boost".equals(keyValuePair[0])) {
                        mlt.setBoost(Boolean.parseBoolean(keyValuePair[1]));
                    } else if ("mlt.qf".equals(keyValuePair[0])) {
                        mlt.setBoostFactor(Float.parseFloat(keyValuePair[1]));
                    } else if ("mlt.maxdf".equals(keyValuePair[0])) {
                        mlt.setMaxDocFreq(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxdfp".equals(keyValuePair[0])) {
                        mlt.setMaxDocFreqPct(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxntp".equals(keyValuePair[0])) {
                        mlt.setMaxNumTokensParsed(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxqt".equals(keyValuePair[0])) {
                        mlt.setMaxQueryTerms(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.maxwl".equals(keyValuePair[0])) {
                        mlt.setMaxWordLen(Integer.parseInt(keyValuePair[1]));
                    } else if ("mlt.minwl".equals(keyValuePair[0])) {
                        mlt.setMinWordLen(Integer.parseInt(keyValuePair[1]));
                    }
                }
            }
            if (text != null) {
                moreLikeThisQuery = mlt.like(new StringReader(text), mlt.getFieldNames()[0]);
            }
            return moreLikeThisQuery;
        } catch (Exception e) {
            throw new RuntimeException("could not handle MLT query " + mltQueryString);
        }
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Related Classes of org.apache.lucene.queries.mlt.MoreLikeThis$FreqQ

  • org.apache.jackrabbit.oak.plugins.index.lucene.util.MoreLikeThisHelper
  • org.apache.lucene.analysis.tokenattributes.CharTermAttribute
  • org.apache.lucene.analysis.TokenStream
  • org.apache.lucene.classification.KNearestNeighborClassifier
  • org.apache.lucene.document.Document
  • org.apache.lucene.index.Fields
  • org.apache.lucene.index.IndexableField
  • org.apache.lucene.index.Term
  • org.apache.lucene.index.Terms
  • org.apache.lucene.index.TermsEnum
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