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- W3004838828 abstract "This paper describes the solution of the POLINKS team to the RecSys Challenge 2019 that focuses on the task of predicting the last click-out in a session-based interaction. We propose an ensemble approach comprising a matrix factorization for modeling the interaction user-item, and a session-aware learning model implemented with a recurrent neural network. This method appears to be effective in predicting the last click-out scoring a 0.60277 of Mean Reciprocal Rank on the local test set." @default.
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- W3004838828 date "2020-02-08" @default.
- W3004838828 modified "2023-09-27" @default.
- W3004838828 title "Predict your Click-out: Modeling User-Item Interactions and Session Actions in an Ensemble Learning Fashion." @default.
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