Item Recommendation Platform
(Redirected from Item(s) Recommendation Platform)
An Item Recommendation Platform is an information filtering platform that can be used to implement an item(s) recommendation system (to solve an item(s) recommendation task).
- Context:
- It can range from being a Python-based Recommendation Platform, R-based Recommendation Platform, ..., Spark-based Recommender, ...
- It can be based on an Item(s) Recommendation Framework.
- Example(s):
- Counter-Example(s):
- …
- See: Personalized Item(s) Recommendations, Contextual Item(s) Recommendation.
References
2017
- https://github.com/ludovikcoba/rrecsys
- QUOTE: A package for R that provides implementations of several popular recommendation systems. They can process standard recommendation datasets (user/item matrix) as input and generate rating predictions and recommendation lists. Standard algorithm implementations included in this package are: Global/Item/User-Average baselines, Item-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology for recommender systems using measures such as MAE, RMSE, Precision, Recall, AUC, [[NDCG, RankScore and coverage measures. The package is intended for rapid prototyping of recommendation algorithms and education purposes.