Personalized Recommendation Algorithm
(Redirected from Personalized Item Recommendations Algorithm)
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A Personalized Recommendation Algorithm is a recommendations algorithm that is a personalized ranking algorithm.
- Context:
- It can be implemented by a Personalized Recommendation System (that solves a personalized recommendation task).
- It can (typically) be a Data-Driven Personalized Item Recommendations Algorithm.
- It can range from being a Micro-Personalized Item Recommendation Algorithm to being a Macro-Personalized Item Recommendation Algorithm.
- It can range from being a Contextual Personalized Item Recommendation Algorithm to being a Non-Contextual Personalized Item Recommendation Algorithm.
- It can range from being a Realtime Personalized Item Recommendation Algorithm to being a Lag-Timed Personalized Item Recommendation Algorithm.
- It can range from being a Session-Aware Personalized Item Recommendation Algorithm to being a Non-Session-Aware Personalized Item Recommendation Algorithm.
- …
- Example(s):
- Collaborative Filtering Algorithm, implemented in a data-driven item recommendations system.
- …
- Counter-Example(s):
- See: Personalized Web Search Algorithm.
References
2018
- (Wang et al., 2018) ⇒ Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie, and Tat-Seng Chua. (2018). “TEM: Tree-enhanced Embedding Model for Explainable Recommendation.” In: Proceedings of the 2018 World Wide Web Conference.
- QUOTE: ... While collaborative filtering is the dominant technique in personalized recommendation, it models user-item interactions only and cannot provide concrete reasons for a recommendation. ...