Neighborhood-based Models¶

Elliot integrates, to date, 50 recommendation models partitioned into two sets. The first set includes 38 popular models implemented in at least two of frameworks reviewed in this work (i.e., adopting a framework-wise popularity notion).

Summary¶

`item_knn.item_knn.ItemKNN`(data, config, …)	Amazon.com recommendations: item-to-item collaborative filtering
`user_knn.user_knn.UserKNN`(data, config, …)	GroupLens: An Open Architecture for Collaborative Filtering of Netnews
`attribute_item_knn.attribute_item_knn.AttributeItemKNN`(…)	Attribute Item-kNN proposed in MyMediaLite Recommender System Library
`attribute_user_knn.attribute_user_knn.AttributeUserKNN`(…)	Attribute User-kNN proposed in MyMediaLite Recommender System Library

ItemKNN¶

class elliot.recommender.NN.item_knn.item_knn.ItemKNN(data, config, params, *args, **kwargs)[source]¶

Bases: elliot.recommender.recommender_utils_mixin.RecMixin, elliot.recommender.base_recommender_model.BaseRecommenderModel

Amazon.com recommendations: item-to-item collaborative filtering

For further details, please refer to the paper

Parameters

neighbors – Number of item neighbors
similarity – Similarity function
implementation – Implementation type (‘aiolli’, ‘classical’)

To include the recommendation model, add it to the config file adopting the following pattern:

models:
  ItemKNN:
    meta:
      save_recs: True
    neighbors: 40
    similarity: cosine
    implementation: aiolli

UserKNN¶

class elliot.recommender.NN.user_knn.user_knn.UserKNN(data, config, params, *args, **kwargs)[source]¶

Bases: elliot.recommender.recommender_utils_mixin.RecMixin, elliot.recommender.base_recommender_model.BaseRecommenderModel

GroupLens: An Open Architecture for Collaborative Filtering of Netnews

For further details, please refer to the paper

Parameters

neighbors – Number of item neighbors
similarity – Similarity function
implementation – Implementation type (‘aiolli’, ‘classical’)

To include the recommendation model, add it to the config file adopting the following pattern:

models:
  UserKNN:
    meta:
      save_recs: True
    neighbors: 40
    similarity: cosine
    implementation: aiolli

AttributeItemKNN¶

class elliot.recommender.NN.attribute_item_knn.attribute_item_knn.AttributeItemKNN(data, config, params, *args, **kwargs)[source]¶

Bases: elliot.recommender.recommender_utils_mixin.RecMixin, elliot.recommender.base_recommender_model.BaseRecommenderModel

Attribute Item-kNN proposed in MyMediaLite Recommender System Library

For further details, please refer to the paper

Parameters

neighbors – Number of item neighbors
similarity – Similarity function

To include the recommendation model, add it to the config file adopting the following pattern:

models:
  AttributeItemKNN:
    meta:
      save_recs: True
    neighbors: 40
    similarity: cosine

AttributeUserKNN¶

class elliot.recommender.NN.attribute_user_knn.attribute_user_knn.AttributeUserKNN(data, config, params, *args, **kwargs)[source]¶

Bases: elliot.recommender.recommender_utils_mixin.RecMixin, elliot.recommender.base_recommender_model.BaseRecommenderModel

Attribute User-kNN proposed in MyMediaLite Recommender System Library

For further details, please refer to the paper

Parameters

neighbors – Number of item neighbors
similarity – Similarity function
profile – Profile type (‘binary’, ‘tfidf’)

To include the recommendation model, add it to the config file adopting the following pattern:

models:
  AttributeUserKNN:
    meta:
      save_recs: True
    neighbors: 40
    similarity: cosine
    profile: binary