List of usage examples for org.apache.mahout.cf.taste.impl.similarity UncenteredCosineSimilarity UncenteredCosineSimilarity
public UncenteredCosineSimilarity(DataModel dataModel, Weighting weighting) throws TasteException
From source file:norbert.mynemo.core.recommendation.recommender.ItemSimilarityRecommender.java
License:Apache License
@Override public Recommender buildRecommender(DataModel dataModel) throws TasteException { checkArgument(dataModel != null, "Data model type must not be null."); ItemSimilarity similarity = null;//from w ww . ja va 2 s .c o m switch (selectedSimilarity) { case ITEM_SIMILARITY_WITH_CITY_BLOCK_DISTANCE: similarity = new CityBlockSimilarity(dataModel); break; case ITEM_SIMILARITY_WITH_EUCLIDEAN_DISTANCE: similarity = new EuclideanDistanceSimilarity(dataModel, Weighting.UNWEIGHTED); break; case ITEM_SIMILARITY_WITH_LOG_LIKELIHOOD: similarity = new LogLikelihoodSimilarity(dataModel); break; case ITEM_SIMILARITY_WITH_PEARSON_CORRELATION: similarity = new PearsonCorrelationSimilarity(dataModel, Weighting.UNWEIGHTED); break; case ITEM_SIMILARITY_WITH_TANIMOTO_COEFFICIENT: similarity = new TanimotoCoefficientSimilarity(dataModel); break; case ITEM_SIMILARITY_WITH_UNCENTERED_COSINE: similarity = new UncenteredCosineSimilarity(dataModel, Weighting.UNWEIGHTED); break; case ITEM_SIMILARITY_WITH_WEIGHTED_EUCLIDEAN_DISTANCE: similarity = new EuclideanDistanceSimilarity(dataModel, Weighting.WEIGHTED); break; case ITEM_SIMILARITY_WITH_WEIGHTED_PEARSON_CORRELATION: similarity = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED); break; case ITEM_SIMILARITY_WITH_WEIGHTED_UNCENTERED_COSINE: similarity = new UncenteredCosineSimilarity(dataModel, Weighting.WEIGHTED); break; default: throw new IllegalStateException(); } int cacheSize = Math.min(dataModel.getNumItems() * dataModel.getNumItems(), MAXIMUM_CACHE_SIZE); similarity = new CachingItemSimilarity(similarity, cacheSize); return new GenericItemBasedRecommender(dataModel, similarity); }
From source file:norbert.mynemo.core.recommendation.recommender.UserSimilarityRecommender.java
License:Apache License
private UserSimilarity createSimilarity(DataModel dataModel) throws TasteException { UserSimilarity selectedSimilarity;/*ww w. j a va 2s . co m*/ switch (configuration.getType()) { case USER_SIMILARITY_WITH_CITY_BLOCK_DISTANCE: selectedSimilarity = new CityBlockSimilarity(dataModel); break; case USER_SIMILARITY_WITH_EUCLIDEAN_DISTANCE: selectedSimilarity = new EuclideanDistanceSimilarity(dataModel, Weighting.UNWEIGHTED); break; case USER_SIMILARITY_WITH_LOG_LIKELIHOOD: selectedSimilarity = new LogLikelihoodSimilarity(dataModel); break; case USER_SIMILARITY_WITH_ORIGINAL_SPEARMAN_CORRELATION: selectedSimilarity = new OriginalSpearmanCorrelationSimilarity(dataModel); break; case USER_SIMILARITY_WITH_PEARSON_CORRELATION: selectedSimilarity = new PearsonCorrelationSimilarity(dataModel, Weighting.UNWEIGHTED); break; case USER_SIMILARITY_WITH_SPEARMAN_CORRELATION: selectedSimilarity = new SpearmanCorrelationSimilarity(dataModel); break; case USER_SIMILARITY_WITH_TANIMOTO_COEFFICIENT: selectedSimilarity = new TanimotoCoefficientSimilarity(dataModel); break; case USER_SIMILARITY_WITH_UNCENTERED_COSINE: selectedSimilarity = new UncenteredCosineSimilarity(dataModel, Weighting.UNWEIGHTED); break; case USER_SIMILARITY_WITH_WEIGHTED_EUCLIDEAN_DISTANCE: selectedSimilarity = new EuclideanDistanceSimilarity(dataModel, Weighting.WEIGHTED); break; case USER_SIMILARITY_WITH_WEIGHTED_PEARSON_CORRELATION: selectedSimilarity = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED); break; case USER_SIMILARITY_WITH_WEIGHTED_UNCENTERED_COSINE: selectedSimilarity = new UncenteredCosineSimilarity(dataModel, Weighting.WEIGHTED); break; default: throw new IllegalStateException(); } int cacheSize = Math.min(dataModel.getNumUsers() * dataModel.getNumUsers(), MAXIMUM_CACHE_SIZE); return new CachingUserSimilarity(selectedSimilarity, cacheSize); }