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Towards universal sequence representation learning for recommender systems
In order to develop effective sequential recommenders, a series of sequence representation
learning (SRL) methods are proposed to model historical user behaviors. Most existing SRL …
learning (SRL) methods are proposed to model historical user behaviors. Most existing SRL …
Learning vector-quantized item representation for transferable sequential recommenders
Recently, the generality of natural language text has been leveraged to develop transferable
recommender systems. The basic idea is to employ pre-trained language models (PLM) to …
recommender systems. The basic idea is to employ pre-trained language models (PLM) to …
Recbole 2.0: Towards a more up-to-date recommendation library
In order to support the study of recent advances in recommender systems, this paper
presents an extended recommendation library consisting of eight packages for up-to-date …
presents an extended recommendation library consisting of eight packages for up-to-date …
Harnessing large language models for text-rich sequential recommendation
Z Zheng, W Chao, Z Qiu, H Zhu, H ** session dataset for recommendation and text generation
Modeling customer shop** intentions is a crucial task for e-commerce, as it directly
impacts user experience and engagement. Thus, accurately understanding customer …
impacts user experience and engagement. Thus, accurately understanding customer …
Linrec: Linear attention mechanism for long-term sequential recommender systems
Transformer models have achieved remarkable success in sequential recommender
systems (SRSs). However, computing the attention matrix in traditional dot-product attention …
systems (SRSs). However, computing the attention matrix in traditional dot-product attention …
A comprehensive review of recommender systems: Transitioning from theory to practice
Recommender Systems (RS) play an integral role in enhancing user experiences by
providing personalized item suggestions. This survey reviews the progress in RS inclusively …
providing personalized item suggestions. This survey reviews the progress in RS inclusively …
Graph and sequential neural networks in session-based recommendation: A survey
Recent years have witnessed the remarkable success of recommendation systems (RSs) in
alleviating the information overload problem. As a new paradigm of RSs, session-based …
alleviating the information overload problem. As a new paradigm of RSs, session-based …
Towards a more user-friendly and easy-to-use benchmark library for recommender systems
In recent years, the reproducibility of recommendation models has become a severe
concern in recommender systems. In light of this challenge, we have previously released a …
concern in recommender systems. In light of this challenge, we have previously released a …
Large language models for intent-driven session recommendations
The goal of intent-aware session recommendation (ISR) approaches is to capture user
intents within a session for accurate next-item prediction. However, the capability of these …
intents within a session for accurate next-item prediction. However, the capability of these …