Example usage for org.apache.lucene.queries.mlt MoreLikeThis setMaxQueryTerms

List of usage examples for org.apache.lucene.queries.mlt MoreLikeThis setMaxQueryTerms

Introduction

In this page you can find the example usage for org.apache.lucene.queries.mlt MoreLikeThis setMaxQueryTerms.

Prototype

public void setMaxQueryTerms(int maxQueryTerms) 

Source Link

Document

Sets the maximum number of query terms that will be included in any generated query.

Usage

From source file:com.qwazr.search.query.MoreLikeThisQuery.java

License:Apache License

@Override
final public Query getQuery(QueryContext queryContext) throws IOException, ParseException {
    Objects.requireNonNull(doc_num, "The doc_num field is missing");
    final MoreLikeThis mlt = new MoreLikeThis(queryContext.indexSearcher.getIndexReader());
    if (is_boost != null)
        mlt.setBoost(is_boost);//from ww w . j  av  a2 s  . c  o  m
    if (boost_factor != null)
        mlt.setBoostFactor(boost_factor);
    if (fieldnames != null)
        mlt.setFieldNames(fieldnames);
    if (max_doc_freq != null)
        mlt.setMaxDocFreq(max_doc_freq);
    if (max_doc_freq_pct != null)
        mlt.setMaxDocFreqPct(max_doc_freq_pct);
    if (max_num_tokens_parsed != null)
        mlt.setMaxNumTokensParsed(max_num_tokens_parsed);
    if (max_query_terms != null)
        mlt.setMaxQueryTerms(max_query_terms);
    if (max_word_len != null)
        mlt.setMaxWordLen(max_word_len);
    if (min_doc_freq != null)
        mlt.setMinDocFreq(min_doc_freq);
    if (min_term_freq != null)
        mlt.setMinTermFreq(min_term_freq);
    if (min_word_len != null)
        mlt.setMinWordLen(min_word_len);
    if (stop_words != null)
        mlt.setStopWords(stop_words);
    mlt.setAnalyzer(queryContext.analyzer);
    return mlt.like(doc_num);
}

From source file:org.apache.jackrabbit.oak.plugins.index.lucene.util.MoreLikeThisHelper.java

License:Apache License

public static Query getMoreLikeThis(IndexReader reader, Analyzer analyzer, String mltQueryString) {
    Query moreLikeThisQuery = null;
    MoreLikeThis mlt = new MoreLikeThis(reader);
    mlt.setAnalyzer(analyzer);/*from w w w  . j a v  a  2s  .c  o m*/
    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[fieldNames.size()]);
                    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);
    }
}

From source file:org.apache.solr.handler.RedbubbleMoreLikeThisHandler.java

License:Apache License

private void setMLTparams(SolrParams params, String[] similarityFields, MoreLikeThis mlt) {
    mlt.setMinTermFreq(params.getInt(MoreLikeThisParams.MIN_TERM_FREQ, MoreLikeThis.DEFAULT_MIN_TERM_FREQ));
    mlt.setMinDocFreq(params.getInt(MoreLikeThisParams.MIN_DOC_FREQ, MoreLikeThis.DEFAULT_MIN_DOC_FREQ));
    mlt.setMaxDocFreq(params.getInt(MoreLikeThisParams.MAX_DOC_FREQ, MoreLikeThis.DEFAULT_MAX_DOC_FREQ));
    mlt.setMinWordLen(params.getInt(MoreLikeThisParams.MIN_WORD_LEN, MoreLikeThis.DEFAULT_MIN_WORD_LENGTH));
    mlt.setMaxWordLen(params.getInt(MoreLikeThisParams.MAX_WORD_LEN, MoreLikeThis.DEFAULT_MAX_WORD_LENGTH));
    mlt.setMaxQueryTerms(
            params.getInt(MoreLikeThisParams.MAX_QUERY_TERMS, MoreLikeThis.DEFAULT_MAX_QUERY_TERMS));
    mlt.setMaxNumTokensParsed(params.getInt(MoreLikeThisParams.MAX_NUM_TOKENS_PARSED,
            MoreLikeThis.DEFAULT_MAX_NUM_TOKENS_PARSED));
    mlt.setBoost(params.getBool(MoreLikeThisParams.BOOST, false));
    mlt.setFieldNames(similarityFields);
}

From source file:org.cee.store.lucene.LuceneArticleStore.java

License:Apache License

private Query createRelatedArticlesQuery(List<EntityKey> sites, ArticleKey reference, IndexSearcher searcher,
        String language) throws IOException {
    Query articleQuery = createArticleQuery(reference);
    TopDocs topDocs = searcher.search(articleQuery, 1);
    if (topDocs.totalHits == 0) {
        return new BooleanQuery(true);
    }//w ww.  j av a 2  s.c  o  m
    MoreLikeThis mlt = new MoreLikeThis(searcher.getIndexReader());
    mlt.setFieldNames(LuceneConstants.ARTICLE_RELATED_SEARCH_FIELDS);
    mlt.setMaxQueryTerms(20);
    mlt.setBoost(true);
    mlt.setMinTermFreq(0);
    mlt.setMinDocFreq(0);
    Query relatedQuery = boostRelatedQuery(mlt.like(topDocs.scoreDocs[0].doc));

    BooleanQuery query = new BooleanQuery();
    query.add(new BooleanClause(relatedQuery, Occur.MUST));
    query.add(new BooleanClause(createQueryArticlesOfSites(sites), Occur.MUST));
    return query;
}

From source file:org.elasticsearch.common.lucene.search.morelikethis.XMoreLikeThisTests.java

License:Apache License

@Test
public void testTopN() throws Exception {
    int numDocs = 100;
    int topN = 25;

    // add series of docs with terms of decreasing df
    Directory dir = newDirectory();// w w w  . j  a  v a2  s .  c  o  m
    RandomIndexWriter writer = new RandomIndexWriter(random(), dir);
    for (int i = 0; i < numDocs; i++) {
        addDoc(writer, generateStrSeq(0, i + 1));
    }
    IndexReader reader = writer.getReader();
    writer.close();

    // setup MLT query
    MoreLikeThis mlt = new MoreLikeThis(reader);
    mlt.setAnalyzer(new MockAnalyzer(random(), MockTokenizer.WHITESPACE, false));
    mlt.setMaxQueryTerms(topN);
    mlt.setMinDocFreq(1);
    mlt.setMinTermFreq(1);
    mlt.setMinWordLen(1);
    mlt.setFieldNames(new String[] { "text" });

    // perform MLT query
    String likeText = "";
    for (String text : generateStrSeq(0, numDocs)) {
        likeText += text + " ";
    }
    BooleanQuery query = (BooleanQuery) mlt.like("text", new StringReader(likeText));

    // check best terms are topN of highest idf
    List<BooleanClause> clauses = query.clauses();
    assertEquals("Expected" + topN + "clauses only!", topN, clauses.size());

    Term[] expectedTerms = new Term[topN];
    int idx = 0;
    for (String text : generateStrSeq(numDocs - topN, topN)) {
        expectedTerms[idx++] = new Term("text", text);
    }
    for (BooleanClause clause : clauses) {
        Term term = ((TermQuery) clause.getQuery()).getTerm();
        assertTrue(Arrays.asList(expectedTerms).contains(term));
    }

    // clean up
    reader.close();
    dir.close();
}

From source file:org.elasticsearch.common.lucene.search.MoreLikeThisQuery.java

License:Apache License

@Override
public Query rewrite(IndexReader reader) throws IOException {
    MoreLikeThis mlt = new MoreLikeThis(reader, similarity == null ? new DefaultSimilarity() : similarity);

    mlt.setFieldNames(moreLikeFields);//from   w w  w  . j  a  v a2 s  . co m
    mlt.setAnalyzer(analyzer);
    mlt.setMinTermFreq(minTermFrequency);
    mlt.setMinDocFreq(minDocFreq);
    mlt.setMaxDocFreq(maxDocFreq);
    mlt.setMaxQueryTerms(maxQueryTerms);
    mlt.setMinWordLen(minWordLen);
    mlt.setMaxWordLen(maxWordLen);
    mlt.setStopWords(stopWords);
    mlt.setBoost(boostTerms);
    mlt.setBoostFactor(boostTermsFactor);
    //LUCENE 4 UPGRADE this mapps the 3.6 behavior (only use the first field)
    BooleanQuery bq = (BooleanQuery) mlt.like(new FastStringReader(likeText), moreLikeFields[0]);
    BooleanClause[] clauses = bq.getClauses();

    bq.setMinimumNumberShouldMatch((int) (clauses.length * percentTermsToMatch));

    bq.setBoost(getBoost());
    return bq;
}

From source file:org.eu.bitzone.Leia.java

License:Apache License

/** More Like this query from the current doc (or selected fields) */
public void actionMLT(final Object docNum, final Object docTable) {
    if (ir == null) {
        errorMsg(MSG_NOINDEX);// www .  j a  v a 2s  . co  m
        return;
    }
    int id = 0;
    try {
        id = Integer.parseInt(getString(docNum, "text"));
    } catch (final NumberFormatException nfe) {
        errorMsg("Invalid document number");
        return;
    }
    final MoreLikeThis mlt = new MoreLikeThis(ir);
    try {
        mlt.setFieldNames(Util.fieldNames(ir, true).toArray(new String[0]));
    } catch (final Exception e) {
        errorMsg("Exception collecting field names: " + e.toString());
        return;
    }
    mlt.setMinTermFreq(1);
    mlt.setMaxQueryTerms(50);
    final Analyzer a = createAnalyzer(find("srchOptTabs"));
    if (a == null) {
        return;
    }
    mlt.setAnalyzer(a);
    final Object[] rows = getSelectedItems(docTable);
    BooleanQuery similar = null;
    if (rows != null && rows.length > 0) {
        // collect text from fields
        final StringBuilder sb = new StringBuilder();
        for (int i = 0; i < rows.length; i++) {
            final Field f = (Field) getProperty(rows[i], "field");
            if (f == null) {
                continue;
            }
            final 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(new StringReader(sb.toString()), "field");
        } catch (final Exception e) {
            e.printStackTrace();
            errorMsg("FAILED: " + e.getMessage());
            return;
        }
    } else {
        try {
            similar = (BooleanQuery) mlt.like(id);
        } catch (final Exception e) {
            e.printStackTrace();
            errorMsg("FAILED: " + e.getMessage());
            return;
        }
    }
    if (similar.clauses() != null && similar.clauses().size() > 0) {
        // System.err.println("SIMILAR: " + similar);
        final Object tabpane = find("maintpane");
        setInteger(tabpane, "selected", 2);
        final Object qField = find("qField");
        setString(qField, "text", similar.toString());
    } else {
        showStatus("WARN: empty query - check Analyzer settings");
    }
}

From source file:org.getopt.luke.Luke.java

License:Apache License

/** More Like this query from the current doc (or selected fields) */
public void actionMLT(Object docNum, Object docTable) {
    if (ir == null) {
        errorMsg(MSG_NOINDEX);// w  w w. j  a  v a 2s  .  co  m
        return;
    }
    int id = 0;
    try {
        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(new StringReader(sb.toString()), "field");
        } 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;
        }
    }
    if (similar.clauses() != null && similar.clauses().size() > 0) {
        //System.err.println("SIMILAR: " + similar);
        Object tabpane = find("maintpane");
        setInteger(tabpane, "selected", 2);
        Object qField = find("qField");
        setString(qField, "text", similar.toString());
    } else {
        showStatus("WARN: empty query - check Analyzer settings");
    }
}

From source file:org.ohdsi.usagi.UsagiSearchEngine.java

License:Apache License

public List<ScoredConcept> search(String searchTerm, boolean useMlt, Collection<Integer> filterConceptIds,
        String filterDomain, String filterConceptClass, String filterVocabulary, boolean filterInvalid) {
    List<ScoredConcept> results = new ArrayList<ScoredConcept>();
    try {/* w  w w .  j a  v a2  s . c  o m*/
        Query query;
        if (useMlt) {
            MoreLikeThis mlt = new MoreLikeThis(searcher.getIndexReader());
            mlt.setMinTermFreq(1);
            mlt.setMinDocFreq(1);
            mlt.setMaxDocFreq(9999);
            mlt.setMinWordLen(1);
            mlt.setMaxWordLen(9999);
            mlt.setMaxDocFreqPct(100);
            mlt.setMaxNumTokensParsed(9999);
            mlt.setMaxQueryTerms(9999);
            mlt.setStopWords(null);
            mlt.setFieldNames(new String[] { "TERM" });
            mlt.setAnalyzer(analyzer);

            query = mlt.like("TERM", new StringReader(searchTerm));
        } else {
            try {
                query = keywordsQueryParser.parse(searchTerm);
                // if (query instanceof BooleanQuery) {
                // List<BooleanClause> clauses = ((BooleanQuery) query).clauses();
                // BooleanClause lastClause = clauses.get(clauses.size() - 1);
                // lastClause.setQuery(new PrefixQuery(((TermQuery) lastClause.getQuery()).getTerm()));
                // } else if (query instanceof TermQuery) {// It's a single term
                // query = new PrefixQuery(((TermQuery) query).getTerm());
                // }

            } catch (ParseException e) {
                return results;
            }
        }

        BooleanQuery booleanQuery = new BooleanQuery();
        booleanQuery.add(query, Occur.SHOULD);
        booleanQuery.add(conceptQuery, Occur.MUST);

        if (filterConceptIds != null && filterConceptIds.size() > 0) {
            Query conceptIdQuery = conceptIdQueryParser.parse(StringUtilities.join(filterConceptIds, " OR "));
            booleanQuery.add(conceptIdQuery, Occur.MUST);
        }

        if (filterDomain != null) {
            Query domainQuery = domainQueryParser.parse("\"" + filterDomain + "\"");
            booleanQuery.add(domainQuery, Occur.MUST);
        }
        if (filterConceptClass != null) {
            Query conceptClassQuery = conceptClassQueryParser
                    .parse("\"" + filterConceptClass.toString() + "\"");
            booleanQuery.add(conceptClassQuery, Occur.MUST);
        }
        if (filterVocabulary != null) {
            Query vocabularyQuery = vocabularyQueryParser.parse("\"" + filterVocabulary.toString() + "\"");
            booleanQuery.add(vocabularyQuery, Occur.MUST);
        }
        if (filterInvalid) {
            Query invalidQuery = invalidQueryParser.parse("\"\"");
            booleanQuery.add(invalidQuery, Occur.MUST);
        }
        TopDocs topDocs = searcher.search(booleanQuery, 100);

        recomputeScores(topDocs.scoreDocs, query);
        for (ScoreDoc scoreDoc : topDocs.scoreDocs) {
            Document document = reader.document(scoreDoc.doc);
            int conceptId = Integer.parseInt(document.get("CONCEPT_ID"));
            // If matchscore = 0 but it was the one concept that was automatically selected, still allow it:
            if (scoreDoc.score > 0 || (filterConceptIds != null && filterConceptIds.size() == 1
                    && filterConceptIds.contains(conceptId))) {
                TargetConcept targetConcept = new TargetConcept();
                targetConcept.term = document.get("TERM");
                targetConcept.conceptId = conceptId;
                targetConcept.conceptName = document.get("CONCEPT_NAME");
                targetConcept.conceptClass = document.get("CONCEPT_CLASS");
                targetConcept.vocabulary = document.get("VOCABULARY");
                targetConcept.conceptCode = document.get("CONCEPT_CODE");
                targetConcept.validStartDate = document.get("VALID_START_DATE");
                targetConcept.validEndDate = document.get("VALID_END_DATE");
                targetConcept.invalidReason = document.get("INVALID_REASON");
                for (String domain : document.get("DOMAINS").split("\n"))
                    targetConcept.domains.add(domain);
                targetConcept.additionalInformation = document.get("ADDITIONAL_INFORMATION");
                results.add(new ScoredConcept(scoreDoc.score, targetConcept));
            }
        }
        reorderTies(results);
        removeDuplicateConcepts(results);
    } catch (Exception e) {
        System.err.println(e.getMessage());
        e.printStackTrace();
    }

    return results;
}