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Found 4 papers, 0 papers with code
Personalized Category Frequency prediction for Buy It Again recommendations
We propose a recommendation system called a hierarchical PCIC model that consists of a personalized category model (PC model) and a personalized item model within categories (IC model).
An Opportunistic Bandit Approach for User Interface Experimentation
In fact, we model user interface experimentation as an opportunistic bandit problem, in which the cost of exploration varies under a factor extracted from customer features.
SWAG: Item Recommendations using Convolutions on Weighted Graphs
Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks.
WEAC: Word embeddings for anomaly classification from event logs
For example, an unusual network activity such as a store transaction server logging into dropbox. com would be automatically flagged as anomalous because of the wrong feature associations for entries in the corresponding event log.
