Example usage for org.apache.mahout.cf.taste.impl.common FastIDSet toArray

Introduction

In this page you can find the example usage for org.apache.mahout.cf.taste.impl.common FastIDSet toArray.

Prototype

public long[] toArray() 

Source Link

Usage

From source file:com.predictionmarketing.itemrecommend.CliMF.java

License:Apache License

private void splitReplyIDs(long userID, Usersitemidset idset) throws TasteException {
    FastIDSet itemids = dataModel.getItemIDsFromUser(userID);
    FastIDSet replyids = new FastIDSet();
    FastIDSet noreplyids = new FastIDSet();
    for (long item : itemids) {
        long writer = postwriter.get(item);
        if (dataModel.getPreferenceValue(userID, item) > 0) {
            if (testuser == userID && writer == coveruser) {//testusercoveruser information
                Total_Test_records++;/*from   w  w  w . j a  v  a 2 s  .c o m*/
            } else {
                replyids.add(item);
            }
        } else {
            noreplyids.add(item);
        }
    }
    if (userID == testuser) {
        left_records += replyids.size();
    }
    Total_records += replyids.size();
    idset.setReplyidset(replyids.toArray());
    idset.setNoreplyidset(noreplyids.toArray());
}

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From source file:com.yelp.recommend.RestaurantSimilarity.java

License:Apache License

@Override
public long[] allSimilarItemIDs(long itemID) {
    FastIDSet allSimilarItemIDs = new FastIDSet();
    LongPrimitiveIterator allItemIDs = RestaurantData.keySetIterator();
    while (allItemIDs.hasNext()) {
        long possiblySimilarItemID = allItemIDs.nextLong();
        if (!Double.isNaN(itemSimilarity(itemID, possiblySimilarItemID))) {
            allSimilarItemIDs.add(possiblySimilarItemID);
        }//from w  w w .  ja v  a  2s  .c  o m
    }
    return allSimilarItemIDs.toArray();
}

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From source file:io.prediction.engines.base.mahout.AllValidItemsCandidateItemsStrategy.java

License:Apache License

@Override
public FastIDSet getCandidateItems(long userID, PreferenceArray preferencesFromUser, DataModel dataModel)
        throws TasteException {
    long[] seenItemIDs;
    if (this.seenDataMap != null) {
        FastIDSet ids = seenDataMap.get(userID);
        if (ids != null) {
            seenItemIDs = ids.toArray();
        } else {/*from w w w . j a  va2  s  . c  om*/
            // user doesn't have any seen action
            seenItemIDs = null;
        }
    } else {
        seenItemIDs = null;
    }

    return doGetCandidateItemsInternal(this.validItemIDs, seenItemIDs);
}

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From source file:org.easyrec.mahout.EasyrecInMemoryDataModelTest.java

License:Open Source License

@Test
public void testEasyrecDataModel_getItemIDsFromUser() throws TasteException {
    DataModel easyrecDataModel = new EasyrecDataModel(TENANT_ID, RATE_ACTION_TYPE_ID, HAS_RATING_VALUES,
            mahoutDataModelMappingDAO);//  w  ww .  jav a  2s.  co  m
    easyrecDataModel = new EasyrecInMemoryDataModel(easyrecDataModel);

    FastIDSet itemIds = easyrecDataModel.getItemIDsFromUser(1);
    long[] itemIdsArray = itemIds.toArray();
    String ids = "";

    for (long itemId : itemIdsArray) {
        ids += itemId;
    }

    assertEquals("123", ids);
}

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

License:Apache License

public static List<RecommendedItem> getTopItems(int howMany, int numThreads, FastIDSet possibleItemIDs,
        final IDRescorer rescorer, final TopItems.Estimator<Long> estimator) throws TasteException {

    Preconditions.checkArgument(numThreads > 1);
    Preconditions.checkNotNull(possibleItemIDs);
    Preconditions.checkNotNull(estimator);

    //long s = System.currentTimeMillis();

    long[] itemIDsToEstimate = possibleItemIDs.toArray();

    //long d = System.currentTimeMillis() - s;
    //System.out.println("Preparation " + d);

    //s = System.currentTimeMillis();
    ExecutorService queue = Executors.newFixedThreadPool(numThreads);

    int fromIndex = 0;
    List<EstimationWorker> estimatorWorkers = Lists.newArrayListWithCapacity(numThreads);
    for (int n = 0; n < numThreads; n++) {

        int toIndex = Math.min(fromIndex + itemIDsToEstimate.length / numThreads, itemIDsToEstimate.length);
        EstimationWorker worker = new EstimationWorker(howMany, itemIDsToEstimate, fromIndex, toIndex, rescorer,
                estimator);/*from w  w w . j a v a  2  s. c  om*/
        estimatorWorkers.add(worker);
        queue.execute(worker);
        fromIndex = toIndex;
    }

    queue.shutdown();
    try {
        queue.awaitTermination(5, TimeUnit.SECONDS);
    } catch (InterruptedException e) {
        throw new RuntimeException(e);
    }
    //d = System.currentTimeMillis() - s;
    //System.out.println("Estimation " + d);

    List<RecommendedItem> topItems = Lists.newArrayList();
    for (int n = 0; n < numThreads; n++) {
        topItems.addAll(estimatorWorkers.get(n).topItems);
    }

    if (topItems.isEmpty()) {
        return Collections.EMPTY_LIST;
    }
    if (topItems.size() < howMany) {
        howMany = topItems.size();
    }
    Collections.sort(topItems, ByValueRecommendedItemComparator.getInstance());
    List<RecommendedItem> recommendedItems = topItems.subList(0, howMany);

    return recommendedItems;
}

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