Recommender Systems (RecSys)
GPTKB entity
Statements (61)
Predicate | Object |
---|---|
gptkbp:instanceOf |
gptkb:technology
information filtering system |
gptkbp:abbreviation |
gptkb:Recommender_Systems
|
gptkbp:hasType |
collaborative filtering
content-based filtering hybrid filtering |
https://www.w3.org/2000/01/rdf-schema#label |
Recommender Systems (RecSys)
|
gptkbp:relatedTo |
gptkb:artificial_intelligence
gptkb:machine_learning gptkb:Amazon_recommendation_engine gptkb:Netflix_Prize gptkb:RecSys_conference gptkb:Spotify_recommendation_system gptkb:YouTube_recommendation_system deep learning neural networks privacy diversity precision F1 score personalization recall data mining ranking algorithms scalability fairness long tail novelty matrix factorization cold start problem context-aware recommendation evaluation metrics explainable recommendation explicit data explicit feedback implicit data implicit feedback item profile mean average precision personalized ranking popularity bias root mean square error serendipity session-based recommendation sparsity problem user engagement user modeling user profile user retention user satisfaction user-item interaction |
gptkbp:usedFor |
content filtering
personalized recommendations product recommendations |
gptkbp:usedIn |
gptkb:media
Advertising e-commerce online streaming news websites |
gptkbp:bfsParent |
gptkb:ACM_SIGCHI
|
gptkbp:bfsLayer |
5
|