Netflix recommendation engine
GPTKB entity
Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Recommendation
|
| gptkbp:developedBy |
gptkb:Netflix
|
| https://www.w3.org/2000/01/rdf-schema#label |
Netflix recommendation engine
|
| gptkbp:impact |
increased user engagement
increased watch time reduced churn |
| gptkbp:improves |
Netflix Prize competition
|
| gptkbp:input |
time of day
device type user ratings search queries user viewing history |
| gptkbp:launched |
2006
|
| gptkbp:output |
genre suggestions
personalized home page row ordering thumbnail selection title ranking |
| gptkbp:relatedTo |
gptkb:Netflix_Prize
A/B testing Reinforcement learning Content discovery Scalability Personalized ranking Bandit algorithms Cold start problem Diversity in recommendations Explicit feedback Exploration-exploitation tradeoff Implicit feedback Matrix factorization Personalization algorithms Serendipity in recommendations User interface personalization User retention |
| gptkbp:technology |
gptkb:Java
gptkb:Python gptkb:AWS gptkb:TensorFlow gptkb:Apache_Spark Metaflow |
| gptkbp:updated |
continuously
|
| gptkbp:usedFor |
personalized content recommendations
|
| gptkbp:uses |
gptkb:machine_learning
deep learning collaborative filtering content-based filtering |
| gptkbp:bfsParent |
gptkb:Amazon_recommendation_engine
|
| gptkbp:bfsLayer |
7
|