A survey on session-based recommender systems
Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …
consumption, services, and decision-making in the overloaded information era and digitized …
Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations
In the field of sequential recommendation, deep learning--(DL) based methods have
received a lot of attention in the past few years and surpassed traditional models such as …
received a lot of attention in the past few years and surpassed traditional models such as …
Spatial-temporal interval aware sequential POI recommendation
The past flourishing years of sequential point-of-interest (POI) recommendation began with
the introduction of Self-Attention Network (SAN), which quickly superseded CNN or RNN as …
the introduction of Self-Attention Network (SAN), which quickly superseded CNN or RNN as …
Intention nets: psychology-inspired user choice behavior modeling for next-basket prediction
Human behaviors are complex, which are often observed as a sequence of heterogeneous
actions. In this paper, we take user choices for shopping baskets as a typical case to study …
actions. In this paper, we take user choices for shopping baskets as a typical case to study …
Knowledge-enhanced multi-view graph neural networks for session-based recommendation
Q Chen, Z Guo, J Li, G Li - Proceedings of the 46th International ACM …, 2023 - dl.acm.org
Session-based recommendation (SBR) has received increasing attention to predict the next
item via extracting and integrating both global and local item-item relationships. However …
item via extracting and integrating both global and local item-item relationships. However …
Deep learning-based sequential recommender systems: Concepts, algorithms, and evaluations
What is sequential recommendation? What challenges are traditional sequential
recommendation models facing? How to address these challenges in sequential …
recommendation models facing? How to address these challenges in sequential …
Degree planning with plan-bert: Multi-semester recommendation using future courses of interest
Planning scenarios involving user pre-specified items present themselves frequently in
recommender system domains. Although next-item and next-basket recommendation has …
recommender system domains. Although next-item and next-basket recommendation has …
Spatial-temporal interval aware individual future trajectory prediction
The past flourishing years of sequential location-based services began with the introduction
of the Self-Attention Network (SAN), which quickly superseded CNN or RNN as the state-of …
of the Self-Attention Network (SAN), which quickly superseded CNN or RNN as the state-of …
Multi-view Multi-aspect Neural Networks for Next-basket Recommendation
Next-basket recommendation (NBR) is a type of recommendation that aims to recommend a
set of items to users according to their historical basket sequences. Existing NBR methods …
set of items to users according to their historical basket sequences. Existing NBR methods …
A systematical evaluation for next-basket recommendation algorithms
Next basket recommender systems (NBRs) aim to recommend a user's next (shopping)
basket of items via modeling the user's preferences towards items based on the user's …
basket of items via modeling the user's preferences towards items based on the user's …