org.apache.lucene.queries.mlt.MoreLikeThis Java Examples
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org.apache.lucene.queries.mlt.MoreLikeThis.
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Example #1
Source File: SearchImpl.java From lucene-solr with Apache License 2.0 | 6 votes |
@Override public Query mltQuery(int docid, MLTConfig mltConfig, Analyzer analyzer) { MoreLikeThis mlt = new MoreLikeThis(reader); mlt.setAnalyzer(analyzer); mlt.setFieldNames(mltConfig.getFieldNames()); mlt.setMinDocFreq(mltConfig.getMinDocFreq()); mlt.setMaxDocFreq(mltConfig.getMaxDocFreq()); mlt.setMinTermFreq(mltConfig.getMinTermFreq()); try { return mlt.like(docid); } catch (IOException e) { throw new LukeException("Failed to create MLT query for doc: " + docid); } }
Example #2
Source File: KNearestNeighborClassifier.java From lucene-solr with Apache License 2.0 | 6 votes |
/** * Creates a {@link KNearestNeighborClassifier}. * * @param indexReader the reader on the index to be used for classification * @param analyzer an {@link Analyzer} used to analyze unseen text * @param similarity the {@link Similarity} to be used by the underlying {@link IndexSearcher} or {@code null} * (defaults to {@link org.apache.lucene.search.similarities.BM25Similarity}) * @param query a {@link Query} to eventually filter the docs used for training the classifier, or {@code null} * if all the indexed docs should be used * @param k the no. of docs to select in the MLT results to find the nearest neighbor * @param minDocsFreq {@link MoreLikeThis#minDocFreq} parameter * @param minTermFreq {@link MoreLikeThis#minTermFreq} parameter * @param classFieldName the name of the field used as the output for the classifier * @param textFieldNames the name of the fields used as the inputs for the classifier, they can contain boosting indication e.g. title^10 */ public KNearestNeighborClassifier(IndexReader indexReader, Similarity similarity, Analyzer analyzer, Query query, int k, int minDocsFreq, int minTermFreq, String classFieldName, String... textFieldNames) { this.textFieldNames = textFieldNames; this.classFieldName = classFieldName; this.mlt = new MoreLikeThis(indexReader); this.mlt.setAnalyzer(analyzer); this.mlt.setFieldNames(textFieldNames); this.indexSearcher = new IndexSearcher(indexReader); if (similarity != null) { this.indexSearcher.setSimilarity(similarity); } else { this.indexSearcher.setSimilarity(new BM25Similarity()); } if (minDocsFreq > 0) { mlt.setMinDocFreq(minDocsFreq); } if (minTermFreq > 0) { mlt.setMinTermFreq(minTermFreq); } this.query = query; this.k = k; }
Example #3
Source File: MoreLikeThisHandler.java From lucene-solr with Apache License 2.0 | 4 votes |
public MoreLikeThisHelper( SolrParams params, SolrIndexSearcher searcher ) { this.searcher = searcher; this.reader = searcher.getIndexReader(); this.uniqueKeyField = searcher.getSchema().getUniqueKeyField(); this.needDocSet = params.getBool(FacetParams.FACET,false); SolrParams required = params.required(); String[] fl = required.getParams(MoreLikeThisParams.SIMILARITY_FIELDS); List<String> list = new ArrayList<>(); for (String f : fl) { if (!StringUtils.isEmpty(f)) { String[] strings = splitList.split(f); for (String string : strings) { if (!StringUtils.isEmpty(string)) { list.add(string); } } } } String[] fields = list.toArray(new String[list.size()]); if( fields.length < 1 ) { throw new SolrException( SolrException.ErrorCode.BAD_REQUEST, "MoreLikeThis requires at least one similarity field: "+MoreLikeThisParams.SIMILARITY_FIELDS ); } this.mlt = new MoreLikeThis( reader ); // TODO -- after LUCENE-896, we can use , searcher.getSimilarity() ); mlt.setFieldNames(fields); mlt.setAnalyzer( searcher.getSchema().getIndexAnalyzer() ); // configurable params 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 ) ); // There is no default for maxDocFreqPct. Also, it's a bit oddly expressed as an integer value // (percentage of the collection's documents count). We keep Lucene's convention here. if (params.getInt(MoreLikeThisParams.MAX_DOC_FREQ_PCT) != null) { mlt.setMaxDocFreqPct(params.getInt(MoreLikeThisParams.MAX_DOC_FREQ_PCT)); } boostFields = SolrPluginUtils.parseFieldBoosts(params.getParams(MoreLikeThisParams.QF)); }
Example #4
Source File: MoreLikeThisHandler.java From lucene-solr with Apache License 2.0 | 4 votes |
public MoreLikeThis getMoreLikeThis() { return mlt; }
Example #5
Source File: LuceneIndexer.java From MtgDesktopCompanion with GNU General Public License v3.0 | 4 votes |
public Map<MagicCard,Float> similarity(MagicCard mc) throws IOException { Map<MagicCard,Float> ret = new LinkedHashMap<>(); if(mc==null) return ret; if(dir==null) open(); logger.debug("search similar cards for " + mc); try (IndexReader indexReader = DirectoryReader.open(dir)) { IndexSearcher searcher = new IndexSearcher(indexReader); Query query = new QueryParser("text", analyzer).parse("name:\""+mc.getName()+"\""); logger.trace(query); TopDocs top = searcher.search(query, 1); if(top.totalHits.value>0) { MoreLikeThis mlt = new MoreLikeThis(indexReader); mlt.setFieldNames(getArray(FIELDS)); mlt.setAnalyzer(analyzer); mlt.setMinTermFreq(getInt(MIN_TERM_FREQ)); mlt.setBoost(getBoolean(BOOST)); ScoreDoc d = top.scoreDocs[0]; logger.trace("found doc id="+d.doc); Query like = mlt.like(d.doc); logger.trace("mlt="+Arrays.asList(mlt.retrieveInterestingTerms(d.doc))); logger.trace("Like query="+like); TopDocs likes = searcher.search(like,getInt(MAX_RESULTS)); for(ScoreDoc l : likes.scoreDocs) ret.put(serializer.fromJson(searcher.doc(l.doc).get("data"),MagicCard.class),l.score); logger.debug("found " + likes.scoreDocs.length + " results"); close(); } else { logger.error("can't found "+mc); } } catch (ParseException e) { logger.error(e); } return ret; }
Example #6
Source File: ContextAnalyzerIndex.java From modernmt with Apache License 2.0 | 4 votes |
public ContextVector getContextVector(UUID user, LanguageDirection direction, Corpus queryDocument, int limit, Rescorer rescorer) throws IOException { String contentFieldName = DocumentBuilder.makeContentFieldName(direction); IndexSearcher searcher = this.getIndexSearcher(); IndexReader reader = searcher.getIndexReader(); // Get matching documents int rawLimit = limit < MIN_RESULT_BATCH ? MIN_RESULT_BATCH : limit; MoreLikeThis mlt = new MoreLikeThis(reader); mlt.setFieldNames(new String[]{contentFieldName}); mlt.setMinDocFreq(0); mlt.setMinTermFreq(1); mlt.setMinWordLen(2); mlt.setBoost(true); mlt.setAnalyzer(analyzer); TopScoreDocCollector collector = TopScoreDocCollector.create(rawLimit, true); Reader queryDocumentReader = queryDocument.getRawContentReader(); try { Query mltQuery = mlt.like(contentFieldName, queryDocumentReader); BooleanQuery ownerQuery = new BooleanQuery(); if (user == null) { ownerQuery.add(DocumentBuilder.makePublicOwnerMatchingQuery(), BooleanClause.Occur.MUST); } else { ownerQuery.add(DocumentBuilder.makePublicOwnerMatchingQuery(), BooleanClause.Occur.SHOULD); ownerQuery.add(DocumentBuilder.makeOwnerMatchingQuery(user), BooleanClause.Occur.SHOULD); ownerQuery.setMinimumNumberShouldMatch(1); } FilteredQuery query = new FilteredQuery(mltQuery, new QueryWrapperFilter(ownerQuery)); searcher.search(query, collector); } finally { IOUtils.closeQuietly(queryDocumentReader); } ScoreDoc[] topDocs = collector.topDocs().scoreDocs; // Rescore result if (rescorer != null) { Document referenceDocument = DocumentBuilder.newInstance(direction, queryDocument); rescorer.rescore(reader, this.analyzer, topDocs, referenceDocument, contentFieldName); } // Build result ContextVector.Builder resultBuilder = new ContextVector.Builder(topDocs.length); resultBuilder.setLimit(limit); for (ScoreDoc topDocRef : topDocs) { Document topDoc = searcher.doc(topDocRef.doc); long memory = DocumentBuilder.getMemory(topDoc); resultBuilder.add(memory, topDocRef.score); } return resultBuilder.build(); }