Equivariant contrastive learning for sequential recommendation
Contrastive learning (CL) benefits the training of sequential recommendation models with
informative self-supervision signals. Existing solutions apply general sequential data …
informative self-supervision signals. Existing solutions apply general sequential data …
Enhancing sequential recommendation with contrastive generative adversarial network
Sequential recommendation models a user's historical sequence to predict future items.
Existing studies utilize deep learning methods and contrastive learning for data …
Existing studies utilize deep learning methods and contrastive learning for data …
Evolution of deep learning-based sequential recommender systems: from current trends to new perspectives
The recommender system which gets higher in practical use in applying the Apriori
algorithm in the early 2000s has revolutionized our daily life as it currently is widely used by …
algorithm in the early 2000s has revolutionized our daily life as it currently is widely used by …
TiCoSeRec: Augmenting data to uniform sequences by time intervals for effective recommendation
Sequential recommendation has now been more widely studied, characterized by its well-
consistency with real-world recommendation situations. Most existing works model user …
consistency with real-world recommendation situations. Most existing works model user …
Sequential recommendation with bidirectional chronological augmentation of transformer
Sequential recommendation can capture user chronological preferences from their historical
behaviors, yet the learning of short sequences (cold-start problem) in many benchmark …
behaviors, yet the learning of short sequences (cold-start problem) in many benchmark …
Enhancing Multi-View Smoothness for Sequential Recommendation Models
Sequential recommendation models aim to predict the interested items to a user based on
his historical behaviors. To train sequential recommenders, implicit feedback data is widely …
his historical behaviors. To train sequential recommenders, implicit feedback data is widely …
MobileRec: A large scale dataset for mobile apps recommendation
Recommender systems have become ubiquitous in our digital lives, from recommending
products on e-commerce websites to suggesting movies and music on streaming platforms …
products on e-commerce websites to suggesting movies and music on streaming platforms …
[HTML][HTML] A meta-adversarial framework for cross-domain cold-start recommendation
Y Liu, S Wang, X Li, F Sun - Data Science and Engineering, 2024 - Springer
The cold-start problem in recommender systems has been facing a great challenge. Cross-
domain recommendation can improve the performance of cold-start user recommendations …
domain recommendation can improve the performance of cold-start user recommendations …
Generating Negative Samples for Sequential Recommendation
To make Sequential Recommendation (SR) successful, recent works focus on designing
effective sequential encoders, fusing side information, and mining extra positive self …
effective sequential encoders, fusing side information, and mining extra positive self …
Multi-Head multimodal deep interest recommendation network
M Yang, P Zhou, S Li, Y Zhang, J Hu… - Knowledge-Based Systems, 2023 - Elsevier
From machine learning recommendation to deep learning recommendation, reinforcement
learning recommendation, and recommendation model compression, the network structure …
learning recommendation, and recommendation model compression, the network structure …