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

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

Introduction

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

Prototype

public void setMinWordLen(int minWordLen) 

Source Link

Document

Sets the minimum word length below which words will be ignored.

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  w  w  w.  java2 s.  co 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  ww w . ja  v  a 2 s  . co 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(//from   w ww.  ja  va 2s . c om
            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.apache.solr.search.mlt.CloudMLTQParser.java

License:Apache License

public Query parse() {
    String id = localParams.get(QueryParsing.V);
    // Do a Real Time Get for the document
    SolrDocument doc = getDocument(id);//from   w  ww. j a  va  2s  .c  o m

    MoreLikeThis mlt = new MoreLikeThis(req.getSearcher().getIndexReader());
    // TODO: Are the mintf and mindf defaults ok at 1/0 ?

    mlt.setMinTermFreq(localParams.getInt("mintf", 1));
    mlt.setMinDocFreq(localParams.getInt("mindf", 0));
    if (localParams.get("minwl") != null)
        mlt.setMinWordLen(localParams.getInt("minwl"));

    if (localParams.get("maxwl") != null)
        mlt.setMaxWordLen(localParams.getInt("maxwl"));

    mlt.setAnalyzer(req.getSchema().getIndexAnalyzer());

    String[] qf = localParams.getParams("qf");
    Map<String, Collection<Object>> filteredDocument = new HashMap();

    if (qf != null) {
        mlt.setFieldNames(qf);
        for (String field : qf) {
            filteredDocument.put(field, doc.getFieldValues(field));
        }
    } else {
        Map<String, SchemaField> fields = req.getSchema().getFields();
        ArrayList<String> fieldNames = new ArrayList();
        for (String field : doc.getFieldNames()) {
            // Only use fields that are stored and have an explicit analyzer.
            // This makes sense as the query uses tf/idf/.. for query construction.
            // We might want to relook and change this in the future though.
            if (fields.get(field).stored() && fields.get(field).getType().isExplicitAnalyzer()) {
                fieldNames.add(field);
                filteredDocument.put(field, doc.getFieldValues(field));
            }
        }
        mlt.setFieldNames(fieldNames.toArray(new String[fieldNames.size()]));
    }

    try {
        return mlt.like(filteredDocument);
    } catch (IOException e) {
        e.printStackTrace();
        throw new SolrException(SolrException.ErrorCode.BAD_REQUEST, "Bad Request");
    }

}

From source file:org.apache.solr.search.mlt.SimpleMLTQParser.java

License:Apache License

public Query parse() {

    String defaultField = req.getSchema().getUniqueKeyField().getName();
    String uniqueValue = localParams.get(QueryParsing.V);
    String[] qf = localParams.getParams("qf");

    SolrIndexSearcher searcher = req.getSearcher();
    Query docIdQuery = createIdQuery(defaultField, uniqueValue);

    try {//  w w w. java2  s . c om
        TopDocs td = searcher.search(docIdQuery, 1);
        if (td.totalHits != 1)
            throw new SolrException(SolrException.ErrorCode.BAD_REQUEST,
                    "Error completing MLT request. Could not fetch " + "document with id [" + uniqueValue
                            + "]");
        ScoreDoc[] scoreDocs = td.scoreDocs;
        MoreLikeThis mlt = new MoreLikeThis(req.getSearcher().getIndexReader());
        // TODO: Are the mintf and mindf defaults ok at '1' ?
        mlt.setMinTermFreq(localParams.getInt("mintf", 1));
        mlt.setMinDocFreq(localParams.getInt("mindf", 1));
        if (localParams.get("minwl") != null)
            mlt.setMinWordLen(localParams.getInt("minwl"));

        if (localParams.get("maxwl") != null)
            mlt.setMaxWordLen(localParams.getInt("maxwl"));

        ArrayList<String> fields = new ArrayList();

        if (qf != null) {
            mlt.setFieldNames(qf);
        } else {

            Map<String, SchemaField> fieldNames = req.getSearcher().getSchema().getFields();
            for (String fieldName : fieldNames.keySet()) {
                if (fieldNames.get(fieldName).indexed() && fieldNames.get(fieldName).stored())
                    if (fieldNames.get(fieldName).getType().getNumericType() == null)
                        fields.add(fieldName);
            }
            mlt.setFieldNames(fields.toArray(new String[fields.size()]));
        }

        mlt.setAnalyzer(req.getSchema().getIndexAnalyzer());

        return mlt.like(scoreDocs[0].doc);

    } catch (IOException e) {
        throw new SolrException(SolrException.ErrorCode.BAD_REQUEST,
                "Error completing MLT request" + e.getMessage());
    }
}

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 va  2s.  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 ava 2 s.c  om*/
    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.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 ww  .j  a v a2s .com
        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;
}