es.uam.eps.ir.ranksys.diversity.binom

Class BinomialModel<U,I,F>

java.lang.Object

es.uam.eps.ir.ranksys.core.model.UserModel<U>

es.uam.eps.ir.ranksys.diversity.binom.BinomialModel<U,I,F>

Type Parameters:

U - type of the users

I - type of the items

F - type of the features

public class BinomialModel<U,I,F>
extends UserModel<U>

Binomial genre diversity model. S. Vargas, L. Baltrunas, A. Karatzoglou, P. Castells. Coverage, redundancy and size-awareness in genre diversity for Recommender Systems. RecSys 2014.

Author:

Saúl Vargas (saul.vargas@uam.es)

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	BinomialModel.UserBinomialModel Binomial diversity model of a user.

Nested classes/interfaces inherited from class es.uam.eps.ir.ranksys.core.model.UserModel

UserModel.Model<U>

Constructor Summary

Constructors

Constructor and Description
BinomialModel(boolean caching, Stream<U> targetUsers, PreferenceData<U,I> recommenderData, FeatureData<I,F,?> featureData, double alpha) Constructor.

Method Summary

Modifier and Type	Method and Description
BinomialModel.UserBinomialModel	get(U u)
Set<F>	getFeatures() Returns the features considered by the model.
BinomialModel.UserBinomialModel	getModel(U u)
double	p(F f) Returns the non-personalized probability of a feature.

Methods inherited from class es.uam.eps.ir.ranksys.core.model.UserModel

initialize

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BinomialModel

public BinomialModel(boolean caching,
                     Stream<U> targetUsers,
                     PreferenceData<U,I> recommenderData,
                     FeatureData<I,F,?> featureData,
                     double alpha)

Constructor.

Parameters:

caching - are the user diversity models cached?

targetUsers - users whose diversity models are cached.

recommenderData - preference data

featureData - feature data

alpha - generality-personalization parameter

Method Detail

getFeatures

public Set<F> getFeatures()

Returns the features considered by the model.

Returns:

the features considered by the model

p

public double p(F f)

Returns the non-personalized probability of a feature.

Parameters:

f - feature

Returns:

non-personalized probability of a feature

get

public BinomialModel.UserBinomialModel get(U u)

Specified by:

get in class UserModel<U>

getModel

public BinomialModel.UserBinomialModel getModel(U u)

Overrides:

getModel in class UserModel<U>