Who will purchase this item next? Reverse next period recommendation in grocery shopping
Recommender systems have become an essential instrument to connect people to the items
that they need. Online grocery shopping is one scenario where this is very clear. So-called …
that they need. Online grocery shopping is one scenario where this is very clear. So-called …
Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions
T Wilm, P Normann, S Baumeister… - Proceedings of the 17th …, 2023 - dl.acm.org
This work introduces TRON, a scalable session-based Transformer Recommender using
Optimized Negative-sampling. Motivated by the scalability and performance limitations of …
Optimized Negative-sampling. Motivated by the scalability and performance limitations of …
To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders
HS Chang, N Agarwal, A McCallum - arXiv preprint arXiv:2310.14079, 2023 - arxiv.org
Recent studies suggest that the existing neural models have difficulty handling repeated
items in sequential recommendation tasks. However, our understanding of this difficulty is …
items in sequential recommendation tasks. However, our understanding of this difficulty is …
Recommender for Its Purpose: Repeat and Exploration in Food Delivery Recommendations
Recommender systems have been widely used for various scenarios, such as e-commerce,
news, and music, providing online contents to help and enrich users' daily life. Different …
news, and music, providing online contents to help and enrich users' daily life. Different …
Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?
Next basket recommendation (NBR) is a special type of sequential recommendation that is
increasingly receiving attention. So far, most NBR studies have focused on optimizing the …
increasingly receiving attention. So far, most NBR studies have focused on optimizing the …
[PDF][PDF] Repetition and Exploration in Offline Reinforcement Learning-based Recommendations
Methods for reinforcement learning for recommendation (RL4Rec) have been gaining a
substantial amount of attention, as they can optimize long-term user engagement. To avoid …
substantial amount of attention, as they can optimize long-term user engagement. To avoid …
TriMLP: A Foundational MLP-like Architecture for Sequential Recommendation
In this work, we present TriMLP as a foundational MLP-like architecture for the sequential
recommendation, simultaneously achieving computational efficiency and promising …
recommendation, simultaneously achieving computational efficiency and promising …