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Interface Summary | |
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ClusterSimilarity | Returns the "similarity" between two clusters of users, according to some definition of similarity. |
TopItems.Estimator<T> |
Class Summary | |
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AbstractCandidateItemsStrategy | Abstract base implementation for retrieving candidate items to recommend |
AbstractRecommender | |
AllSimilarItemsCandidateItemsStrategy | returns the result of ItemSimilarity.allSimilarItemIDs(long) as candidate items |
AllUnknownItemsCandidateItemsStrategy | |
ByValueRecommendedItemComparator | Defines a natural ordering from most-preferred item (highest value) to least-preferred. |
CachingRecommender |
A Recommender which caches the results from another Recommender in memory. |
EstimatedPreferenceCapper | Simple class which encapsulates restricting a preference value to a predefined range. |
FarthestNeighborClusterSimilarity | Defines cluster similarity as the smallest similarity between any two users in the clusters -- that is, it says that clusters are close when all pairs of their members have relatively high similarity. |
GenericBooleanPrefItemBasedRecommender | A variant on GenericItemBasedRecommender which is appropriate for use when no notion of preference
value exists in the data. |
GenericBooleanPrefUserBasedRecommender | A variant on GenericUserBasedRecommender which is appropriate for use when no notion of preference
value exists in the data. |
GenericItemBasedRecommender |
A simple Recommender which uses a given
DataModel and
ItemSimilarity to produce recommendations. |
GenericItemBasedRecommender.MostSimilarEstimator | |
GenericRecommendedItem |
A simple implementation of RecommendedItem . |
GenericUserBasedRecommender |
A simple Recommender
which uses a given DataModel and UserNeighborhood to produce recommendations. |
ItemAverageRecommender | A simple recommender that always estimates preference for an item to be the average of all known preference values for that item. |
ItemUserAverageRecommender |
Like ItemAverageRecommender , except that estimated preferences are adjusted for the users' average
preference value. |
NearestNeighborClusterSimilarity | Defines cluster similarity as the largest similarity between any two users in the clusters -- that is, it says that clusters are close when some pair of their members has high similarity. |
NullRescorer<T> |
A simple Rescorer which always returns the original score. |
PreferredItemsNeighborhoodCandidateItemsStrategy | |
RandomRecommender | Produces random recommendations and preference estimates. |
SamplingCandidateItemsStrategy | Returns all items that have not been rated by the user (3) and that were preferred by another user (2) that has preferred at least one item (1) that the current user has preferred too. |
SimilarUser | Simply encapsulates a user and a similarity value. |
TopItems | A simple class that refactors the "find top N things" logic that is used in several places. |
TreeClusteringRecommender |
A Recommender that clusters users, then determines the
clusters' top recommendations. |
TreeClusteringRecommender2 |
A Recommender that clusters users, then determines the
clusters' top recommendations. |
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