Modifier and Type | Method and Description |
---|---|
void |
Refreshable.refresh(Collection<Refreshable> alreadyRefreshed)
Triggers "refresh" -- whatever that means -- of the implementation.
|
Modifier and Type | Class and Description |
---|---|
class |
RefreshHelper
A helper class for implementing
Refreshable . |
Modifier and Type | Method and Description |
---|---|
static Collection<Refreshable> |
RefreshHelper.buildRefreshed(Collection<Refreshable> currentAlreadyRefreshed)
Creates a new and empty
Collection if the method parameter is null . |
Modifier and Type | Method and Description |
---|---|
void |
RefreshHelper.addDependency(Refreshable refreshable)
Add a dependency to be refreshed first when the encapsulating object does.
|
static void |
RefreshHelper.maybeRefresh(Collection<Refreshable> alreadyRefreshed,
Refreshable refreshable)
Adds the specified
Refreshable to the given collection of Refreshable s if it is not
already there and immediately refreshes it. |
void |
RefreshHelper.removeDependency(Refreshable refreshable) |
Modifier and Type | Method and Description |
---|---|
static Collection<Refreshable> |
RefreshHelper.buildRefreshed(Collection<Refreshable> currentAlreadyRefreshed)
Creates a new and empty
Collection if the method parameter is null . |
static void |
RefreshHelper.maybeRefresh(Collection<Refreshable> alreadyRefreshed,
Refreshable refreshable)
Adds the specified
Refreshable to the given collection of Refreshable s if it is not
already there and immediately refreshes it. |
void |
RefreshHelper.refresh(Collection<Refreshable> alreadyRefreshed)
Typically this is called in
refresh(java.util.Collection) and is the entire body of
that method. |
Modifier and Type | Class and Description |
---|---|
class |
AbstractDataModel
Contains some features common to all implementations.
|
class |
AbstractIDMigrator |
class |
AbstractJDBCIDMigrator
Implementation which stores the reverse long-to-String mapping in a database.
|
class |
GenericBooleanPrefDataModel
A simple
DataModel which uses given user data as its data source. |
class |
GenericDataModel
|
class |
MemoryIDMigrator
Implementation which stores the reverse long-to-String mapping in memory.
|
class |
MySQLJDBCIDMigrator
An implementation for MySQL.
|
class |
PlusAnonymousConcurrentUserDataModel
This is a special thread-safe version of
PlusAnonymousUserDataModel
which allow multiple concurrent anonymous requests. |
class |
PlusAnonymousUserDataModel
|
Modifier and Type | Method and Description |
---|---|
void |
PlusAnonymousUserDataModel.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
GenericDataModel.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
GenericBooleanPrefDataModel.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
AbstractIDMigrator.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Class and Description |
---|---|
class |
FileDataModel
A
DataModel backed by a delimited file. |
class |
FileIDMigrator
An
IDMigrator backed by a file. |
Modifier and Type | Method and Description |
---|---|
void |
FileDataModel.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
FileIDMigrator.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Class and Description |
---|---|
class |
CachingUserNeighborhood
A caching wrapper around an underlying
UserNeighborhood implementation. |
class |
NearestNUserNeighborhood
Computes a neighborhood consisting of the nearest n users to a given user.
|
class |
ThresholdUserNeighborhood
Computes a neigbhorhood consisting of all users whose similarity to the given user meets or exceeds a
certain threshold.
|
Modifier and Type | Method and Description |
---|---|
void |
CachingUserNeighborhood.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractCandidateItemsStrategy
Abstract base implementation for retrieving candidate items to recommend
|
class |
AbstractRecommender |
class |
AllSimilarItemsCandidateItemsStrategy
returns the result of
ItemSimilarity.allSimilarItemIDs(long) as candidate items |
class |
AllUnknownItemsCandidateItemsStrategy |
class |
CachingRecommender
A
Recommender which caches the results from another Recommender in memory. |
class |
GenericBooleanPrefItemBasedRecommender
A variant on
GenericItemBasedRecommender which is appropriate for use when no notion of preference
value exists in the data. |
class |
GenericBooleanPrefUserBasedRecommender
A variant on
GenericUserBasedRecommender which is appropriate for use when no notion of preference
value exists in the data. |
class |
GenericItemBasedRecommender
|
class |
GenericUserBasedRecommender
|
class |
ItemAverageRecommender
A simple recommender that always estimates preference for an item to be the average of all known preference
values for that item.
|
class |
ItemUserAverageRecommender
Like
ItemAverageRecommender , except that estimated preferences are adjusted for the users' average
preference value. |
class |
PreferredItemsNeighborhoodCandidateItemsStrategy |
class |
RandomRecommender
Produces random recommendations and preference estimates.
|
class |
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.
|
Modifier and Type | Method and Description |
---|---|
void |
GenericUserBasedRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
GenericItemBasedRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
CachingRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
ItemAverageRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
RandomRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
ItemUserAverageRecommender.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
AbstractCandidateItemsStrategy.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Interface and Description |
---|---|
interface |
Factorizer
Implementation must be able to create a factorization of a rating matrix
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractFactorizer
base class for
Factorizer s, provides ID to index mapping |
class |
ALSWRFactorizer
factorizes the rating matrix using "Alternating-Least-Squares with Weighted-λ-Regularization" as described in
"Large-scale Collaborative Filtering for the Netflix Prize"
also supports the implicit feedback variant of this approach as described in "Collaborative Filtering for Implicit
Feedback Datasets" available at http://research.yahoo.com/pub/2433
|
class |
ParallelSGDFactorizer
Minimalistic implementation of Parallel SGD factorizer based on
"Scalable Collaborative Filtering Approaches for Large Recommender Systems"
and
"Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent"
|
class |
RatingSGDFactorizer
Matrix factorization with user and item biases for rating prediction, trained with plain vanilla SGD
|
class |
SVDPlusPlusFactorizer
SVD++, an enhancement of classical matrix factorization for rating prediction.
|
class |
SVDRecommender
A
Recommender that uses matrix factorization (a projection of users
and items onto a feature space) |
Modifier and Type | Method and Description |
---|---|
void |
AbstractFactorizer.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
SVDRecommender.refresh(Collection<Refreshable> alreadyRefreshed)
Refresh the data model and factorization.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractItemSimilarity |
class |
AveragingPreferenceInferrer
Implementations of this interface compute an inferred preference for a user and an item that the user has
not expressed any preference for.
|
class |
CachingItemSimilarity
Caches the results from an underlying
ItemSimilarity implementation. |
class |
CachingUserSimilarity
Caches the results from an underlying
UserSimilarity implementation. |
class |
CityBlockSimilarity
Implementation of City Block distance (also known as Manhattan distance) - the absolute value of the difference of
each direction is summed.
|
class |
EuclideanDistanceSimilarity
An implementation of a "similarity" based on the Euclidean "distance" between two users X and Y.
|
class |
GenericItemSimilarity
A "generic"
ItemSimilarity which takes a static list of precomputed item similarities and bases its
responses on that alone. |
class |
GenericUserSimilarity |
class |
LogLikelihoodSimilarity
|
class |
PearsonCorrelationSimilarity
An implementation of the Pearson correlation.
|
class |
SpearmanCorrelationSimilarity
Like
PearsonCorrelationSimilarity , but compares relative ranking of preference values instead of
preference values themselves. |
class |
TanimotoCoefficientSimilarity
An implementation of a "similarity" based on the
Tanimoto coefficient, or extended Jaccard
coefficient.
|
class |
UncenteredCosineSimilarity
An implementation of the cosine similarity.
|
Modifier and Type | Method and Description |
---|---|
void |
AveragingPreferenceInferrer.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
LogLikelihoodSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
CityBlockSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
SpearmanCorrelationSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
AbstractItemSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
TanimotoCoefficientSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
GenericItemSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
CachingItemSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
GenericUserSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
void |
CachingUserSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Class and Description |
---|---|
class |
FileItemSimilarity
An
ItemSimilarity backed by a comma-delimited file. |
Modifier and Type | Method and Description |
---|---|
void |
FileItemSimilarity.refresh(Collection<Refreshable> alreadyRefreshed) |
Modifier and Type | Interface and Description |
---|---|
interface |
DataModel
Implementations represent a repository of information about users and their associated
Preference s
for items. |
interface |
IDMigrator
Mahout 0.2 changed the framework to operate only in terms of numeric (long) ID values for users and items.
|
interface |
JDBCDataModel |
interface |
UpdatableIDMigrator |
Modifier and Type | Interface and Description |
---|---|
interface |
UserNeighborhood
Implementations of this interface compute a "neighborhood" of users like a given user.
|
Modifier and Type | Interface and Description |
---|---|
interface |
CandidateItemsStrategy
Used to retrieve all items that could possibly be recommended to the user
|
interface |
ItemBasedRecommender
Interface implemented by "item-based" recommenders.
|
interface |
MostSimilarItemsCandidateItemsStrategy
Used to retrieve all items that could possibly be similar
|
interface |
Recommender
Implementations of this interface can recommend items for a user.
|
interface |
UserBasedRecommender
Interface implemented by "user-based" recommenders.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ItemSimilarity
Implementations of this interface define a notion of similarity between two items.
|
interface |
PreferenceInferrer
Implementations of this interface compute an inferred preference for a user and an item that the user has
not expressed any preference for.
|
interface |
UserSimilarity
Implementations of this interface define a notion of similarity between two users.
|
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