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Found 3 papers, 1 papers with code
Adaptive Collaborative Filtering with Personalized Time Decay Functions for Financial Product Recommendation
Classical recommender systems often assume that historical data are stationary and fail to account for the dynamic nature of user preferences, limiting their ability to provide reliable recommendations in time-sensitive settings.
History-Augmented Collaborative Filtering for Financial Recommendations
In many businesses, and particularly in finance, the behavior of a client might drastically change over time.
Deep Prediction of Investor Interest: a Supervised Clustering Approach
We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given time frame.
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