org.grouplens.lenskit.basic

Class RescoringItemRecommender

java.lang.Object

org.grouplens.lenskit.basic.RescoringItemRecommender

All Implemented Interfaces:

ItemRecommender

public class RescoringItemRecommender
extends Object
implements ItemRecommender

Item recommender that wraps another item recommender and replaces its scores.

Since:

2.1

Field Summary

Fields

Modifier and Type	Field and Description
static Symbol	ORIGINAL_SCORE_SYMBOL

Constructor Summary

Constructors

Constructor and Description
RescoringItemRecommender(ItemRecommender rec, ItemScorer score) Create a new rescoring item recommender.

Method Summary

Modifier and Type	Method and Description
List<ScoredId>	recommend(long user) Recommend all possible items for a user using the default exclude set.
List<ScoredId>	recommend(long user, int n) Recommend up to n items for a user using the default exclude set.
List<ScoredId>	recommend(long user, int n, Set<Long> candidates, Set<Long> exclude) Produce a set of recommendations for the user.
List<ScoredId>	recommend(long user, Set<Long> candidates) Recommend all possible items for a user from a set of candidates using the default exclude set.

Methods inherited from class java.lang.Object

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

Field Detail

ORIGINAL_SCORE_SYMBOL

public static final Symbol ORIGINAL_SCORE_SYMBOL

Constructor Detail

RescoringItemRecommender

@Inject
public RescoringItemRecommender(ItemRecommender rec,
                                        ItemScorer score)

Create a new rescoring item recommender.

Parameters:

rec - The recommender.

score - The item scorer.

Method Detail

recommend

public List<ScoredId> recommend(long user)

Description copied from interface: ItemRecommender

Recommend all possible items for a user using the default exclude set.

Specified by:

recommend in interface ItemRecommender

Parameters:

user - The user ID.

Returns:

The recommended items.

See Also:

ItemRecommender.recommend(long, int, Set, Set)

recommend

public List<ScoredId> recommend(long user,
                                int n)

Description copied from interface: ItemRecommender

Recommend up to n items for a user using the default exclude set.

Specified by:

recommend in interface ItemRecommender

Parameters:

user - The user ID.

n - The number of recommendations to return.

Returns:

The recommended items.

See Also:

ItemRecommender.recommend(long, int, Set, Set)

recommend

public List<ScoredId> recommend(long user,
                                @Nullable
                                Set<Long> candidates)

Description copied from interface: ItemRecommender

Recommend all possible items for a user from a set of candidates using the default exclude set.

Specified by:

recommend in interface ItemRecommender

Parameters:

user - The user ID.

candidates - The candidate set (can be null to represent the universe).

Returns:

The recommended items.

See Also:

ItemRecommender.recommend(long, int, Set, Set)

recommend

public List<ScoredId> recommend(long user,
                                int n,
                                @Nullable
                                Set<Long> candidates,
                                @Nullable
                                Set<Long> exclude)

Description copied from interface: ItemRecommender

Produce a set of recommendations for the user. This is the most general recommendation method, allowing the recommendations to be constrained by both a candidate set and an exclude set. The exclude set is applied to the candidate set, so the final effective candidate set is canditates minus exclude.

Specified by:

recommend in interface ItemRecommender

Parameters:

user - The user's ID

n - The number of ratings to return. If negative, there is no specific recommendation list size requested.

candidates - A set of candidate items which can be recommended. If null, all items are considered candidates.

exclude - A set of items to be excluded. If null, a default exclude set is used.

Returns:

A list of recommended items. If the recommender cannot assign meaningful scores, the scores will be Double.NaN. For most scoring recommenders, the items will be ordered in decreasing order of score. This is not a hard requirement — e.g. set recommenders are allowed to be more flexible.