Java Code Examples for pitt.search.semanticvectors.SearchResult

The following examples show how to use pitt.search.semanticvectors.SearchResult. These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
public <T extends Comparable<T>>void searchTermsUsingTermQuery(T termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> termTransform,int numResults)
{
	lock.readLock().lock();
	try
	{
		String query = termTransform.toSV(termQuery);
		LinkedList<SearchResult> results = search(query,termVecReader,termVecReader,numResults);
		for(SearchResult r : results)
		{
			String filename = r.getObjectVector().getObject().toString();
			docResult.add(new SemVectorResult<>(termTransform.fromSV(filename),r.getScore()));
		}
	}
	finally
	{
		lock.readLock().unlock();
	}
}
 
Example 2
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
public <T extends Comparable<T>,L extends Comparable<L>>void searchDocsUsingTermQuery(L termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,QueryTransform<L> termTransform,int numResults)
{
	lock.readLock().lock();
	try
	{
		String query = termTransform.toSV(termQuery); 
		LinkedList<SearchResult> results = search(query,termVecReader,docVecReader,numResults);
		for(SearchResult r : results)
		{
			String filename = r.getObjectVector().getObject().toString();
			docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
		}
	}
	finally
	{
		lock.readLock().unlock();
	}
}
 
Example 3
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
public <T extends Comparable<T>>void recommendDocsUsingDocQuery(T docQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,int numResults,Set<T> exclusions,T minDoc)
{
	lock.readLock().lock();
	try
	{
		String docName = docTransform.toSV(docQuery);
		Set<String> docExclusions = new HashSet<>();
		for(T i : exclusions)
			docExclusions.add(docTransform.toSV(i));
		LinkedList<SearchResult> results = recommend(docName,docVecReader,docVecReader,numResults,docExclusions,new HashSet<String>(),docTransform.toSV(minDoc));
		for(SearchResult r : results)
		{
			String filename = r.getObjectVector().getObject().toString();
			docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
		}
	}
	finally
	{
		lock.readLock().unlock();
	}
}
 
Example 4
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
public <T extends Comparable<T>>void searchDocsUsingDocQuery(T termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,int numResults)
{
	lock.readLock().lock();
	try
	{
		String docName = docTransform.toSV(termQuery);
		LinkedList<SearchResult> results = search(docName,docVecReader,docVecReader,numResults);
		for(SearchResult r : results)
		{
			String filename = r.getObjectVector().getObject().toString();
			docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
		}
	}
	finally
	{
		lock.readLock().unlock();
	}
}
 
Example 5
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
private LinkedList<SearchResult> search(String query,VectorStore queryStore,VectorStore searchStore,int numResults)
{
	 VectorSearcher vecSearcher;
	 LinkedList<SearchResult> results = new LinkedList<>();
	 try 
	 {
		 String[] queryTerms = query.split("\\s+");
		 vecSearcher =
	            new VectorSearcher.VectorSearcherCosine(queryStore,
	                                                    searchStore,
	                                                    luceneUtils,
	                                                    flagConfig,
	                                                    queryTerms);
		 results = vecSearcher.getNearestNeighbors(numResults);
		 
		 
	 } catch (pitt.search.semanticvectors.vectors.ZeroVectorException e) {
		 results = new LinkedList<>();

	}
	 return results;
}
 
Example 6
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
private LinkedList<SearchResult> recommend(String query,VectorStore queryStore,VectorStore searchStore,int numResults,Set<String> exclusions,Set<String> inclusions,String minDoc)
{

	 LinkedList<SearchResult> results = new LinkedList<>();
	 try 
	 {
		 String[] queryTerms = query.split("\\s+");
		 VectorStoreRecommender vecSearcher =
	            new VectorStoreRecommender.VectorStoreRecommenderCosine(queryStore,
	                                                    searchStore,
	                                                    luceneUtils,
	                                                    queryTerms,
	                                                    exclusions,
	                                                    inclusions,
	                                                    minDoc);
		 results = vecSearcher.getNearestNeighbors(numResults);
		 
		 
	 } catch (ZeroVectorException zve) {
		 results = new LinkedList<>();
	 }
	 return results;
}
 
Example 7
Source Project: seldon-server   Source File: SemVectorsPeer.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Find similar users by querying the docstore using a query from the terms passed in
 * @param <T>
 * @param terms
 * @param lUtils : lucene utils
 * @param numResults : max number of results to return
 * @param docResult : the result list of return ids T
 * @param docTransform : the transform from document to return id type T
 */
public <T extends Comparable<T>> void findSimilarUsersFromTerms(String[] terms,LuceneUtils lUtils,int numResults,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform)
{
	List<SearchResult> results;
	try 
	{
		VectorSearcher vecSearcher =
	            new VectorSearcher.VectorSearcherCosine(termVecReader,
	                                                    docVecReader,
	                                                    luceneUtils,
	                                                    flagConfig,
	                                                    terms);
		results = vecSearcher.getNearestNeighbors(numResults);
	} 
	catch (pitt.search.semanticvectors.vectors.ZeroVectorException e) {
		results = new LinkedList<>();
	}
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		
		docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 8
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 6 votes vote down vote up
private LinkedList<SearchResult> search(String query,VectorStore queryStore,VectorStore searchStore,int numResults)
{
	 VectorSearcher vecSearcher;
	 LinkedList<SearchResult> results = new LinkedList<>();
	 try 
	 {
		 String[] queryTerms = query.split("\\s+");
		 vecSearcher =
	            new VectorSearcher.VectorSearcherCosine(queryStore,
	                                                    searchStore,
	                                                    luceneUtils,
	                                                    flagConfig,
	                                                    queryTerms);
		 results = vecSearcher.getNearestNeighbors(numResults);
		 
		 
	 } catch (pitt.search.semanticvectors.vectors.ZeroVectorException e) {
		 results = new LinkedList<>();

	}
	 return results;
}
 
Example 9
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 6 votes vote down vote up
private LinkedList<SearchResult> recommend(String query,VectorStore queryStore,VectorStore searchStore,int numResults,Set<String> exclusions,Set<String> inclusions,String minDoc)
{

	 LinkedList<SearchResult> results = new LinkedList<>();
	 try 
	 {
		 String[] queryTerms = query.split("\\s+");
		 VectorStoreRecommender vecSearcher =
	            new VectorStoreRecommender.VectorStoreRecommenderCosine(queryStore,
	                                                    searchStore,
	                                                    luceneUtils,
	                                                    queryTerms,
	                                                    exclusions,
	                                                    inclusions,
	                                                    minDoc);
		 results = vecSearcher.getNearestNeighbors(numResults);
		 
		 
	 } catch (ZeroVectorException e) {
		 results = new LinkedList<>();
	}
	 finally{}
	 return results;
}
 
Example 10
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Find similar users by querying the docstore using a query from the terms passed in
 * @param <T>
 * @param terms
 * @param lUtils : lucene utils
 * @param numResults : max number of results to return
 * @param docResult : the result list of return ids T
 * @param docTransform : the transform from document to return id type T
 */
public <T extends Comparable<T>> void findSimilarUsersFromTerms(String[] terms,LuceneUtils lUtils,int numResults,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform)
{
	List<SearchResult> results;
	try 
	{
		VectorSearcher vecSearcher =
	            new VectorSearcher.VectorSearcherCosine(termVecReader,
	                                                    docVecReader,
	                                                    luceneUtils,
	                                                    flagConfig,
	                                                    terms);
		results = vecSearcher.getNearestNeighbors(numResults);
	} 
	catch (pitt.search.semanticvectors.vectors.ZeroVectorException e) {
		results = new LinkedList<>();
	}
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		
		docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 11
/**
 * Prints the nearest predicate for a particular flagConfig. (Please extend this comment!)
 *
 * @param flagConfig
 * @throws IOException
 */
public static void printNearestPredicate(FlagConfig flagConfig) throws IOException {
  VerbatimLogger.info("Printing predicate results.");
  Vector queryVector = VectorFactory.createZeroVector(flagConfig.vectortype(), flagConfig.dimension());
  VectorSearcher.VectorSearcherBoundProduct predicateFinder;
  try {
    predicateFinder = new VectorSearcher.VectorSearcherBoundProduct(
        VectorStoreReader.openVectorStore(flagConfig.semanticvectorfile(), flagConfig),
        VectorStoreReader.openVectorStore(flagConfig.boundvectorfile(), flagConfig),
        null, flagConfig, queryVector);
    List<SearchResult> bestPredicate = predicateFinder.getNearestNeighbors(1);
    if (bestPredicate.size() > 0) {
      String pred = bestPredicate.get(0).getObjectVector().getObject().toString();
      System.out.println(pred);
    }
  } catch (ZeroVectorException e) {
    // TODO Auto-generated catch block
    e.printStackTrace();
  }
}
 
Example 12
@Test
public void makeQueryVectorTest() {
  VectorStore vectors = table.getRowVectorStore();
  Assert.assertTrue(vectors.getVector("a").measureOverlap(vectors.getVector("b")) >
      vectors.getVector("a").measureOverlap(vectors.getVector("c")));
  Assert.assertTrue(vectors.getVector("c").measureOverlap(vectors.getVector("b")) >
      vectors.getVector("a").measureOverlap(vectors.getVector("c")));

  Vector queryVector = table.makeCellVector(1, "1600");
  for (SearchResult result : table.searchRowVectors(queryVector)) {
    // System.out.println(result.getScore() + ":" + result.getObjectVector().getObject());
  }

  for (int i = 1600; i <= 1700; i += 20) {
    Vector queryVector2 = table.makeCellVector(1, "" + i);
    System.out.println(i + " : " + queryVector.measureOverlap(queryVector2));
  }
}
 
Example 13
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 5 votes vote down vote up
public <T extends Comparable<T>>void searchTermsUsingTermQuery(T termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> termTransform,int numResults)
{
	String query = termTransform.toSV(termQuery);
	LinkedList<SearchResult> results = search(query,termVecReader,termVecReader,numResults);
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		docResult.add(new SemVectorResult<>(termTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 14
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 5 votes vote down vote up
public <T extends Comparable<T>,L extends Comparable<L>>void searchDocsUsingTermQuery(L termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,QueryTransform<L> termTransform,int numResults)
{
	String query = termTransform.toSV(termQuery); 
	LinkedList<SearchResult> results = search(query,termVecReader,docVecReader,numResults);
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 15
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 5 votes vote down vote up
public <T extends Comparable<T>>void recommendDocsUsingDocQuery(T docQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,int numResults,Set<T> exclusions,T minDoc)
{
	String docName = docTransform.toSV(docQuery);
	Set<String> docExclusions = new HashSet<>();
	for(T i : exclusions)
		docExclusions.add(docTransform.toSV(i));
	LinkedList<SearchResult> results = recommend(docName,docVecReader,docVecReader,numResults,docExclusions,new HashSet<String>(),docTransform.toSV(minDoc));
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 16
Source Project: seldon-server   Source File: SemanticVectorsStore.java    License: Apache License 2.0 5 votes vote down vote up
public <T extends Comparable<T>>void searchDocsUsingDocQuery(T termQuery,ArrayList<SemVectorResult<T>> docResult,QueryTransform<T> docTransform,int numResults)
{
	String docName = docTransform.toSV(termQuery);
	LinkedList<SearchResult> results = search(docName,docVecReader,docVecReader,numResults);
	for(SearchResult r : results)
	{
		String filename = r.getObjectVector().getObject().toString();
		docResult.add(new SemVectorResult<>(docTransform.fromSV(filename),r.getScore()));
	}
}
 
Example 17
/** Experiment in querying for a particular president's name. */
private static void queryForName(Table table, String name) {
  System.out.println("Querying for name: '" + name + "'");
  Vector queryVector = table.getRowVectorStore().getVector(name);
  for (SearchResult result : table.searchRowVectors(queryVector)) {
    System.out.println(result.toTexTableString(20));
  }
}
 
Example 18
private static void outputSuggestions(String query) throws Exception  {
  String[] args = new String[] {
      "-queryvectorfile", "termvectors.bin", "-numsearchresults", "10",
      "-luceneindexpath", "permutation_index",
      query };
  List<SearchResult> results = Search.runSearch(FlagConfig.getFlagConfig(args));

  if (results.size() > 0) {
    for (SearchResult result: results) {
      String suggestion = ((ObjectVector)result.getObjectVector()).getObject().toString();
      logger.finest("query:"+query + " suggestion:" + suggestion + " score:" + result.getScore());
    }
  }
}
 
Example 19
Source Project: seldon-server   Source File: VectorStoreRecommender.java    License: Apache License 2.0 4 votes vote down vote up
/**
 * This nearest neighbor search is implemented in the abstract
 * VectorSearcher class itself: this enables all subclasses to reuse
 * the search whatever scoring method they implement.  Since query
 * expressions are built into the VectorSearcher,
 * getNearestNeighbors no longer takes a query vector as an
 * argument.
 * @param numResults the number of results / length of the result list.
 */
public LinkedList<SearchResult> getNearestNeighbors(int numResults) {
  LinkedList<SearchResult> results = new LinkedList<>();
  double score, threshold = -1;
  int duplicatesRemoved = 0;
  Enumeration<ObjectVector> vecEnum = searchVecStore.getAllVectors();

  while (vecEnum.hasMoreElements()) {
  	
  	ObjectVector testElement = vecEnum.nextElement();
  	
  	// ignore excluded items
  	if (exclusions.contains(testElement.getObject().toString()))
  		continue;
  	
  	//only allow includions if specified
  	if (inclusions != null && inclusions.size()>0 && !inclusions.contains(testElement.getObject().toString()))
  		continue;
  	
  	// ignore items greater than minDoc id (assume doc ids string ordering is useful)
  	if (minDoc != null && testElement.getObject().toString().compareTo(minDoc) < 0)
  		continue;
  	
  	
    // Initialize result list if just starting.
    if (results.size() == 0) {
      score = getScore(testElement.getVector());
      results.add(new SearchResult(score, testElement));
      continue;
    }

    // Test this element.

    score = getScore(testElement.getVector());

    // This is a way of using the Lucene Index to get term and
    // document frequency information to reweight all results. It
    // seems to be good at moving excessively common terms further
    // down the results. Note that using this means that scores
    // returned are no longer just cosine similarities.
    if (this.luceneUtils != null) {
      score = score *
          luceneUtils.getGlobalTermWeightFromString((String) testElement.getObject());
    }

    if (score > threshold) 
    {
      boolean added = false;
      boolean duplicate = false;
      for (int i = 0; i < results.size() && !added && !duplicate; ++i) 
      {
      	SearchResult r = results.get(i);
      	
      	if (score == r.getScore())
      	{
      		ObjectVector rVec = (ObjectVector) r.getObjectVector();
      		double overlap = getScore(rVec.getVector(),testElement.getVector());
      		double epsilon = Math.abs(overlap-1);
      		if (epsilon < 0.000001)
      		{
      			duplicatesRemoved++;
      			duplicate = true;
      			continue;
      		}
      	}
      	// Add to list if this is right place.
      	if (score > r.getScore() && added == false) 
      	{
      		results.add(i, new SearchResult(score, testElement));
      		added = true;
      	}
      }
      // Prune list if there are already numResults.
      if (results.size() > numResults) 
      {
        results.removeLast();
        threshold = results.getLast().getScore();
      } 
      else 
      {
        if (results.size() < numResults && !added && !duplicate) 
        {
          results.add(new SearchResult(score, testElement));
        }
      }
    }
  }
  if (duplicatesRemoved > 0)
  	logger.info("removed "+duplicatesRemoved+" duplicates");
  return results;
}
 
Example 20
/**
	 * Method to process a single analogy
	 * Questions will be skipped if any of the four terms are not present
	 * @return
	 */
	
	
	public void processAnalogy()
	{
		
	String[] queryTerms = inLine.toLowerCase().split(" ");
    
	//not a proportional analogy
	if (queryTerms.length < 4) 
	{
		System.out.println(threadno+": "+inLine+": Skipping line");
		return;
	}
    	
	Vector aTermVector = null;
	Vector bTermVector = null;
	Vector cTermVector = null;

	
	String missingTerms = "";
	if (!termVectors.containsVector(queryTerms[0])) missingTerms = missingTerms + queryTerms[0]+"; ";
	if (!termVectors.containsVector(queryTerms[1])) missingTerms = missingTerms + queryTerms[1]+"; ";
	if (!termVectors.containsVector(queryTerms[2])) missingTerms = missingTerms + queryTerms[2]+"; ";
	if (!termVectors.containsVector(queryTerms[3])) missingTerms = missingTerms + queryTerms[3]+"; ";
	
	if (!missingTerms.isEmpty())
	{
		System.out.println(threadno+": "+"Missing terms "+missingTerms);
		return;
	}
	
	aTermVector = termVectors.getVector(queryTerms[0]);
	bTermVector = termVectors.getVector(queryTerms[1]);
	cTermVector = termVectors.getVector(queryTerms[2]);

	Vector cueVector = bTermVector.copy();
	cueVector.superpose(aTermVector, -1, null);
	cueVector.superpose(cTermVector, +1, null);
	cueVector.normalize();
		
	int rank = 1;
	String object = "";
	
	
	try {
		VectorSearcher.VectorSearcherCosine analogySearcher
		 	 = new VectorSearcher.VectorSearcherCosine(termVectors,termVectors,null, flagConfig, cueVector);
		
		//get top 1000 results plus the three query terms
		LinkedList<SearchResult> results = analogySearcher.getNearestNeighbors(1003);
		
		
		for (SearchResult sr:results)
		{
			object = sr.getObjectVector().getObject().toString();
		
			//result found 
			if (object.equals(queryTerms[3]))
				break;
			
			//ignore query terms
			if (!(object.equals(queryTerms[0])
					|| object.equals(queryTerms[1])
					  || object.equals(queryTerms[2]))
						)
				rank++;
			
		}
		} 	catch (ZeroVectorException e) {
	// TODO Auto-generated catch block
	e.printStackTrace();
	System.out.println(threadno+": "+"Error on example "+ inLine);
}
	
	//calculate reciprocal rank as a more granular metric than accuracy
	double reciprank = 1 / (double) rank;
	if (reciprank < 0.001) reciprank = 0;
	
	examplessubset.incrementAndGet();
	exampletot.incrementAndGet();;
	recipsubset.add(reciprank);
	reciptot.add(reciprank);
	
	//correct result (top ranked other than query terms)
	if (reciprank == 1)
		{
			accsubset.incrementAndGet();;
			acctot.incrementAndGet();;
		}
	
	System.out.println(threadno+": "+inLine +" --> "+object+" "+rank+" "+reciprank);
	
		
}
 
Example 21
public void testQuery(FlagConfig flagConfig, String searchfile, String indexfile, String query )
{
	VectorSearcher vs;
	LuceneUtils lUtils = null;
	CloseableVectorStore queryVecReader, searchVecReader;
	LinkedList<SearchResult> results;
	int numResults = 20;

	BeagleUtils utils = BeagleUtils.getInstance();
	utils.setFFTCacheSize(100);

	try
	{
		queryVecReader = VectorStoreReader.openVectorStore(indexfile, flagConfig);
		searchVecReader = VectorStoreReader.openVectorStore(searchfile, flagConfig);

		//BeagleCompoundVecBuilder bcb = new BeagleCompoundVecBuilder ();

		String[] queryTerms = query.split(" ");

		// Create VectorSearcher and search for nearest neighbors.
		vs = new BeagleVectorSearcher( queryVecReader, searchVecReader, lUtils, flagConfig, queryTerms);
		System.err.print("Searching term vectors, searchtype BEAGLE ... ");
		queryVecReader.close();
		searchVecReader.close();

		results = vs.getNearestNeighbors(numResults);

	}
	catch (Exception e)
	{
		System.err.println(e.getMessage());
		results = new LinkedList<SearchResult>();
	}

	// Print out results.
	if (results.size() > 0) {
		System.err.println("Search output follows ...\n");
		for (SearchResult result: results) {
			System.out.println(result.getScore() + ":" +
                                                  ((ObjectVector)result.getObjectVector()).getObject().toString());
		}
	} else {
		System.err.println("No search output.");
	}
}
 
Example 22
public List<Passage> query(Question question) {
	List<Passage> passages = new ArrayList<>();
	VectorSearcher[] sv_searchers;
	try {
		sv_searchers = new VectorSearcher[]{
				new VectorSearcher.VectorSearcherCosine( 
				        queryVecReader, resultsVecReader, luceneUtils, 
				        fconfig, question.getTokens().toArray(new String[]{})),
		        /*new VectorSearcher.VectorSearcherLucene(luceneUtils, 
				        fconfig, question.getTokens().toArray(new String[]{})),
		        new VectorSearcher.VectorSearcherMaxSim( 
				        queryVecReader, resultsVecReader, luceneUtils, 
				        fconfig, question.getTokens().toArray(new String[]{})),*/
		        new VectorSearcher.VectorSearcherMinSim(
				        queryVecReader, resultsVecReader, luceneUtils, 
				        fconfig, question.getTokens().toArray(new String[]{})),
		        /*new VectorSearcher.VectorSearcherSubspaceSim(
				        queryVecReader, resultsVecReader, luceneUtils, 
				        fconfig, question.getTokens().toArray(new String[]{})),*/
		};
	
		System.out.println("sv_searchers = " + sv_searchers);
		for (VectorSearcher sv_searcher : sv_searchers)
		if (sv_searcher != null) {
			List<SearchResult> results = sv_searcher.getNearestNeighbors(10);
			System.out.println("result = " + results);
			int rank = 0;
			for (SearchResult result: results) {
				passages.add(new Passage(
						"semvec", 											// Engine
						"",	// Title
						"",	// Text
						result.getObjectVector().getObject().toString())													// Reference
						.score("SEMVEC_RANK", (double) rank++)				// Rank
						.score("SEMVEC_SCORE", (double) result.getScore())	// Score
						.score("SEMVEC_PRESENT", 1.0)
						);
			}
		}
		/*sv_searcher = new VectorSearcher.VectorSearcherCosine( 
        queryVecReader, resultsVecReader, luceneUtils, 
        fconfig, question.tokens.toArray(new String[]{}));*/
	} catch (ZeroVectorException e) {
	// TODO: Under what circumstances does this happen?
	e.printStackTrace();
	}
	return fillFromSources(passages);
}