Example usage for org.apache.mahout.cf.taste.recommender IDRescorer isFiltered

Introduction

In this page you can find the example usage for org.apache.mahout.cf.taste.recommender IDRescorer isFiltered.

Prototype

boolean isFiltered(long id);

Source Link

Document

Returns true to exclude the given thing.

Usage

From source file:com.mashup.resys.recommender.TopItems.java

License:Apache License

public static List<RecommendedItem> getTopItems(int howMany, LongPrimitiveIterator possibleItemIDs,
        IDRescorer rescorer, Estimator<Long> estimator) throws TasteException {
    if ((possibleItemIDs == null) || (estimator == null)) {
        throw new IllegalArgumentException("argument is null");
    }/*from w w w . j a  v a  2 s . c o  m*/
    Queue<RecommendedItem> topItems = new PriorityQueue<RecommendedItem>(howMany + 1,
            Collections.reverseOrder(ByValueRecommendedItemComparator.getInstance()));
    boolean full = false;
    double lowestTopValue = Double.NEGATIVE_INFINITY;
    while (possibleItemIDs.hasNext()) {
        long itemID = possibleItemIDs.next();
        if ((rescorer == null) || !rescorer.isFiltered(itemID)) {
            double preference;
            try {
                preference = estimator.estimate(itemID);
            } catch (NoSuchItemException nsie) {
                continue;
            }
            double rescoredPref = rescorer == null ? preference : rescorer.rescore(itemID, preference);

            if (!Double.isNaN(rescoredPref) && (!full || (rescoredPref > lowestTopValue))) {
                topItems.add(new GenericRecommendedItem(itemID, (float) rescoredPref));
                if (full) {
                    topItems.poll();
                } else if (topItems.size() > howMany) {
                    full = true;
                    topItems.poll();
                }
                lowestTopValue = topItems.peek().getValue();
            }
        }
    }
    int size = topItems.size();

    if (size == 0) {
        return Collections.emptyList();
    }
    List<RecommendedItem> result = new ArrayList<RecommendedItem>(size);
    result.addAll(topItems);
    Collections.sort(result, ByValueRecommendedItemComparator.getInstance());
    return result;
}

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From source file:com.mashup.resys.recommender.TopItems.java

License:Apache License

public static long[] getTopUsers(int howMany, LongPrimitiveIterator allUserIDs, IDRescorer rescorer,
        Estimator<Long> estimator) throws TasteException {
    Queue<SimilarUser> topUsers = new PriorityQueue<SimilarUser>(howMany + 1, Collections.reverseOrder());
    boolean full = false;
    double lowestTopValue = Double.NEGATIVE_INFINITY;
    while (allUserIDs.hasNext()) {
        long userID = allUserIDs.next();
        if ((rescorer != null) && rescorer.isFiltered(userID)) {
            continue;
        }/*from  w w  w .j ava2  s.  c o m*/
        double similarity;
        try {
            similarity = estimator.estimate(userID);
        } catch (NoSuchUserException nsue) {
            continue;
        }
        double rescoredSimilarity = rescorer == null ? similarity : rescorer.rescore(userID, similarity);
        if (!Double.isNaN(rescoredSimilarity) && (!full || (rescoredSimilarity > lowestTopValue))) {
            topUsers.add(new SimilarUser(userID, similarity));
            if (full) {
                topUsers.poll();
            } else if (topUsers.size() > howMany) {
                full = true;
                topUsers.poll();
            }
            lowestTopValue = topUsers.peek().getSimilarity();
        }
    }
    int size = topUsers.size();
    if (size == 0) {
        return NO_IDS;
    }
    List<SimilarUser> sorted = new ArrayList<SimilarUser>(size);
    sorted.addAll(topUsers);
    Collections.sort(sorted);
    long[] result = new long[size];
    int i = 0;
    for (SimilarUser similarUser : sorted) {
        result[i++] = similarUser.getUserID();
    }
    return result;
}

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From source file:com.webir.popcornsaver.cluster.TreeClusteringRecommender.java

License:Apache License

@Override
public List<RecommendedItem> recommend(long userID, int howMany, IDRescorer rescorer) throws TasteException {
    Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
    buildClusters();/*from w  w  w  .ja v a  2  s  . c o m*/

    log.debug("Recommending items for user ID '{}'", userID);

    List<RecommendedItem> recommended = topRecsByUserID.get(userID);
    if (recommended == null) {
        return Collections.emptyList();
    }

    DataModel dataModel = getDataModel();
    List<RecommendedItem> rescored = new ArrayList<RecommendedItem>(recommended.size());
    // Only add items the user doesn't already have a preference for.
    // And that the rescorer doesn't "reject".
    for (RecommendedItem recommendedItem : recommended) {
        long itemID = recommendedItem.getItemID();
        if ((rescorer != null) && rescorer.isFiltered(itemID)) {
            continue;
        }
        if ((dataModel.getPreferenceValue(userID, itemID) == null) && ((rescorer == null)
                || !Double.isNaN(rescorer.rescore(itemID, recommendedItem.getValue())))) {
            rescored.add(recommendedItem);
        }
    }
    Collections.sort(rescored, new ByRescoreComparator(rescorer));

    return rescored;
}

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From source file:net.myrrix.online.MostPopularItemsIterator.java

License:Apache License

@Override
public RecommendedItem next() {
    FastByIDFloatMap.MapEntry entry = countsIterator.next();
    long id = entry.getKey();
    float value = entry.getValue();
    IDRescorer theRescorer = rescorer;
    if (theRescorer != null) {
        if (theRescorer.isFiltered(id)) {
            return null;
        }//from w w  w  .  j  a  v a2  s . c  o  m
        value = (float) theRescorer.rescore(id, value);
        if (!LangUtils.isFinite(value)) {
            return null;
        }
    }
    delegate.set(id, value);
    return delegate;
}

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From source file:net.myrrix.online.MultiRescorer.java

License:Apache License

@Override
public boolean isFiltered(long itemID) {
    for (IDRescorer rescorer : rescorers) {
        if (rescorer.isFiltered(itemID)) {
            return true;
        }/*from  w w  w  . j a v  a2s .co  m*/
    }
    return false;
}

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From source file:net.myrrix.online.MultiRescorerProviderTest.java

License:Apache License

@Test
public void testMultiRecommendRescorer() {
    RescorerProvider multi = new MultiRescorerProvider(new SimpleModRescorerProvider(2),
            new SimpleModRescorerProvider(3));

    IDRescorer provider = multi.getRecommendRescorer(new long[] { 5 }, (MyrrixRecommender) null);
    assertNull(provider);/*from   w  w  w  .  ja  v a2  s  .  c om*/

    provider = multi.getRecommendRescorer(new long[] { 2 }, (MyrrixRecommender) null);
    assertNotNull(provider);
    assertFalse(provider instanceof MultiRescorer);
    assertTrue(provider.isFiltered(3));
    assertFalse(provider.isFiltered(2));

    provider = multi.getRecommendRescorer(new long[] { 6 }, (MyrrixRecommender) null);
    assertNotNull(provider);
    assertTrue(provider instanceof MultiRescorer);
    assertTrue(provider.isFiltered(3));
    assertTrue(provider.isFiltered(2));
    assertFalse(provider.isFiltered(12));
}

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From source file:net.myrrix.online.MultiRescorerProviderTest.java

License:Apache License

@Test
public void testMultiRecommendToAnonymousRescorer() {
    RescorerProvider multi = new MultiRescorerProvider(new SimpleModRescorerProvider(2),
            new SimpleModRescorerProvider(3));

    IDRescorer provider = multi.getRecommendToAnonymousRescorer(new long[] { 5 }, (MyrrixRecommender) null);
    assertNull(provider);//from   w ww.  j a v  a  2 s  . co m

    provider = multi.getRecommendToAnonymousRescorer(new long[] { 2 }, (MyrrixRecommender) null);
    assertNotNull(provider);
    assertFalse(provider instanceof MultiRescorer);
    assertTrue(provider.isFiltered(3));
    assertFalse(provider.isFiltered(2));

    provider = multi.getRecommendToAnonymousRescorer(new long[] { 6 }, (MyrrixRecommender) null);
    assertNotNull(provider);
    assertTrue(provider instanceof MultiRescorer);
    assertTrue(provider.isFiltered(3));
    assertTrue(provider.isFiltered(2));
    assertFalse(provider.isFiltered(12));
}

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From source file:net.myrrix.online.MultiRescorerProviderTest.java

License:Apache License

@Test
public void testMultiMostPopularItemsRescorer() {
    RescorerProvider multi = new MultiRescorerProvider(new SimpleModRescorerProvider(2),
            new SimpleModRescorerProvider(3));
    IDRescorer provider = multi.getMostPopularItemsRescorer(null);
    assertNotNull(provider);//from  w w w .j  a v a  2 s. co  m
    assertTrue(provider instanceof MultiRescorer);
    assertTrue(provider.isFiltered(3));
    assertTrue(provider.isFiltered(2));
    assertFalse(provider.isFiltered(6));
}

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From source file:net.myrrix.online.RecommendIterator.java

License:Apache License

@Override
public RecommendedItem next() {
    FastByIDMap.MapEntry<float[]> entry = Yiterator.next();
    long itemID = entry.getKey();

    if (userTagIDs.contains(itemID)) {
        return null;
    }/*  w  w w  . j av a  2s  . c o m*/

    FastIDSet theKnownItemIDs = knownItemIDs;
    if (theKnownItemIDs != null) {
        synchronized (theKnownItemIDs) {
            if (theKnownItemIDs.contains(itemID)) {
                return null;
            }
        }
    }

    IDRescorer rescorer = this.rescorer;
    if (rescorer != null && rescorer.isFiltered(itemID)) {
        return null;
    }

    float[] itemFeatures = entry.getValue();
    double sum = 0.0;
    int count = 0;
    for (float[] oneUserFeatures : features) {
        sum += SimpleVectorMath.dot(itemFeatures, oneUserFeatures);
        count++;
    }

    if (rescorer != null) {
        sum = rescorer.rescore(itemID, sum);
        if (!LangUtils.isFinite(sum)) {
            return null;
        }
    }

    float result = (float) (sum / count);
    Preconditions.checkState(LangUtils.isFinite(result), "Bad recommendation value");
    delegate.set(itemID, result);
    return delegate;
}

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From source file:org.plista.kornakapi.core.recommender.ArrayTopItems.java

License:Apache License

public static List<RecommendedItem> getTopItems(int howMany, long[] possibleItemIDs, int fromIndex, int toIndex,
        IDRescorer rescorer, TopItems.Estimator<Long> estimator) throws TasteException {

    Preconditions.checkArgument(possibleItemIDs != null, "possibleItemIDs is null");
    Preconditions.checkArgument(estimator != null, "estimator is null");

    Queue<RecommendedItem> topItems = new PriorityQueue<RecommendedItem>(howMany + 1,
            Collections.reverseOrder(ByValueRecommendedItemComparator.getInstance()));
    boolean full = false;
    double lowestTopValue = Double.NEGATIVE_INFINITY;
    for (int index = fromIndex; index < toIndex; index++) {
        long itemID = possibleItemIDs[index];
        if (rescorer == null || !rescorer.isFiltered(itemID)) {
            double preference;
            try {
                preference = estimator.estimate(itemID);
            } catch (NoSuchItemException nsie) {
                continue;
            } catch (NoSuchUserException nsue) {
                continue;
            }//from ww w .java  2  s .c om
            double rescoredPref = rescorer == null ? preference : rescorer.rescore(itemID, preference);
            if (!Double.isNaN(rescoredPref) && (!full || rescoredPref > lowestTopValue)) {
                topItems.add(new GenericRecommendedItem(itemID, (float) rescoredPref));
                if (full) {
                    topItems.poll();
                } else if (topItems.size() > howMany) {
                    full = true;
                    topItems.poll();
                }
                lowestTopValue = topItems.peek().getValue();
            }
        }
    }
    int size = topItems.size();
    if (size == 0) {
        return Collections.emptyList();
    }
    List<RecommendedItem> result = Lists.newArrayListWithCapacity(size);
    result.addAll(topItems);
    Collections.sort(result, ByValueRecommendedItemComparator.getInstance());
    return result;
}

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