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CFEngine API | ||||||||||
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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 |
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CFEngine API | ||||||||||
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