CFEngine API

Uses of Class
org.recommender.server.ItemPrediction

Packages that use ItemPrediction
org.recommender.algorithms A wide variety of different implementations of collaborative filtering recommendation and precition algorithms are provided. 
org.recommender.algorithms.Experimental   
org.recommender.server This package contains the core Java recommender server code, including the database access code, the ratings caching code, and code that instantiates algorithms. 
 

Uses of ItemPrediction in org.recommender.algorithms
 

Methods in org.recommender.algorithms that return ItemPrediction
 ItemPrediction[] SimplePearsonAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Yun Wang Return top n recommendations of specific type.
 ItemPrediction[] SimplePearsonAlgorithm.getRecommendations(int activeUser, int n)
          Return top n recommendations.
 ItemPrediction SimplePearsonAlgorithm.predictRating(int activeUser, int item)
          Predicts the rating for the given user and item.
 ItemPrediction CFAlgorithm.predictRating(int userID, int itemID)
          Asks the prediction engine to return a prediction for how a particular user will rate a particular item.
 ItemPrediction[] CFAlgorithm.getRecommendations(int activeUser, int n)
          Return top n recommendations for the active user.
 ItemPrediction[] CFAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Added by Yun Wang Return top n recommendations for the active user of specific type.
 

Uses of ItemPrediction in org.recommender.algorithms.Experimental
 

Methods in org.recommender.algorithms.Experimental that return ItemPrediction
 ItemPrediction[] UserItem2Algorithm.getRecommendationsByType(int activeUser, int n, int type)
          Not yet complete
 ItemPrediction UserItem2Algorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item
 ItemPrediction[] TransNeighborAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Not yet complete
 ItemPrediction[] TransNeighborAlgorithm.getRecommendations(int activeUser, int n)
          Returns top n recommendations.
 ItemPrediction TransNeighborAlgorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item.
 ItemPrediction[] SimpleSVD.getRecommendationsByType(int activeUser, int n, int type)
          Not implemented
 ItemPrediction[] SimpleSVD.getRecommendations(int activeUser, int n)
          Not implemented
 ItemPrediction SimpleSVD.predictRating(int activeUser, int item)
          Simply return the rating in the SVD-reduced matrix
 ItemPrediction[] SVD_Pearson.getRecommendationsByType(int activeUser, int n, int type)
          Not implemented
 ItemPrediction[] SVD_Pearson.getRecommendations(int activeUser, int n)
          Not implemented
 ItemPrediction SVD_Pearson.predictRating(int activeUser, int item)
          Predict ratings using nearest neighbor algorithm -- user correlations are based on the Pearson correlations between users' ratings on "features"
 ItemPrediction[] SVD_Cosine.getRecommendationsByType(int activeUser, int n, int type)
          Not implemented
 ItemPrediction[] SVD_Cosine.getRecommendations(int activeUser, int n)
          Not implemented
 ItemPrediction SVD_Cosine.predictRating(int activeUser, int item)
          Predict ratings using nearest neighbor algorithm -- user correlations are based on the Cosine distance between users' ratings on "features"
 ItemPrediction ContinuousBayesNetAlgorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item.
 ItemPrediction BayesNetAlgorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item.
 ItemPrediction[] VectorSimilarityAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Not yet complete
 ItemPrediction[] VectorSimilarityAlgorithm.getRecommendations(int activeUser, int n)
          Not yet complete
 ItemPrediction VectorSimilarityAlgorithm.predictRating(int activeUser, int item)
          Predict rating for activeUser' item.
 ItemPrediction[] UserItemAlgorithm.getRecommendations(int activeUser, int n)
          Not yet complete.
 ItemPrediction[] UserItemAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Not yet complete
 ItemPrediction UserItemAlgorithm.predictRating(int activeUser, int item)
          Predicts the rating for the given user and item.
 ItemPrediction[] SimpleDistributionAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Return top n recommendations of specific type.
 ItemPrediction[] SimpleDistributionAlgorithm.getRecommendations(int activeUser, int n)
          Return top n recommendations.
 ItemPrediction SimpleDistributionAlgorithm.predictRating(int activeUser, int item)
          Predicts the rating for the given user and item.
 ItemPrediction SimpleDistributionAlgorithm.computeRating(float[] activeDist, float[] difDist, float activeMean, int itemNumber)
          Return the computed prediction
 ItemPrediction[] PopAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Yun Wang Return top n recommendations of specific type.
 ItemPrediction[] PopAlgorithm.getRecommendations(int activeUser, int n)
          Returns top n recommendations.
 ItemPrediction PopAlgorithm.predictRating(int activeUser, int item)
          Predicts the rating for the given user and item.
 ItemPrediction[] PersonalityAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Not yet complete
 ItemPrediction[] PersonalityAlgorithm.getRecommendations(int activeUser, int n)
          Not yet implemented.
 ItemPrediction PersonalityAlgorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item
 ItemPrediction[] ItemItemAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Yun Wang Return top n recommendations of specific type.
 ItemPrediction[] ItemItemAlgorithm.getRecommendations(int activeUser, int n)
          Get top n item recommendations for the activeUser.
 ItemPrediction ItemItemAlgorithm.predictRating(int activeUser, int item)
          predicts the rating for the given user and item
 ItemPrediction HortingAlgorithm.predictRating(int userID, int itemID)
          Get predicted rating for a user's item
 ItemPrediction[] HortingAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Yun Wang Return top n recommendations of specific type.
 ItemPrediction[] HortingAlgorithm.getRecommendations(int activeUser, int n)
          Returns top n recommendations.
 ItemPrediction[] DumbPopAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Yun Wang Return top n recommendations of specific type.
 ItemPrediction[] DumbPopAlgorithm.getRecommendations(int activeUser, int n)
          Returns top n recommendations.
 ItemPrediction DumbPopAlgorithm.predictRating(int activeUser, int item)
           
 ItemPrediction ClusteringAlgorithm.predictRating(int userID, int itemID)
          Asks the prediction engine to return a prediction for how a particular user will rate a particular item.
 ItemPrediction[] ClusteringAlgorithm.getRecommendations(int activeUser, int n)
          Not yet implemented.
 ItemPrediction[] ClusteringAlgorithm.getRecommendationsByType(int activeUser, int n, int type)
          Haven't been implemented yet.
 

Uses of ItemPrediction in org.recommender.server
 

Fields in org.recommender.server declared as ItemPrediction
 ItemPrediction[] UserInfo.userTopN
           
 

Methods in org.recommender.server that return ItemPrediction
 ItemPrediction[] CFEngineImpl.getRecommendations(int userID, int number, int offset)
          Get top n recommendation for user.
 ItemPrediction[] CFEngineImpl.getRecommendationsByType(int userID, int number, int offset, int type)
          Get top n recommendations for current user of specific type.
 ItemPrediction CFEngineImpl.getPredictedRating(int userID, int itemID)
          Get predicted rating for user's item.
 ItemPrediction[] CFEngineImpl.getPredictedRatingList(int userID, int[] itemID)
          Gets predicted ratings for a list of items.
 ItemPrediction CFEngine.getPredictedRating(int userID, int itemID)
          Get a user's predicted rating for an item.
 ItemPrediction[] CFEngine.getRecommendations(int curUser, int number, int offset)
          Get ten items with high predicted ratings for current user.
 ItemPrediction[] CFEngine.getPredictedRatingList(int userID, int[] itemID)
          Gets predicted ratings for a list of items.
 ItemPrediction[] CFEngine.getRecommendationsByType(int curUser, int number, int offset, int type)
          Get top n recommendations for current user of specific type.
 ItemPrediction[] DataManager.getCachedTopN(int userID, int number, int offset)
          Returns a user's top N recommendations, retrieved from the server side memory cache.
 ItemPrediction[] DataManager.getTopNByType(int userID, int number, int offset, int type, ItemPrediction[] pred)
          Returns a user's typed top N recommendations, No caching
 

Methods in org.recommender.server with parameters of type ItemPrediction
 void DataManager.cacheUserTopN(int userID, ItemPrediction[] predictions)
          Cache user TopN data computed by one of our algorithms.
 ItemPrediction[] DataManager.getTopNByType(int userID, int number, int offset, int type, ItemPrediction[] pred)
          Returns a user's typed top N recommendations, No caching
 


CFEngine API

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