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Towards Efficient and Effective Transformers for Sequential Recommendation
Transformer and its variants have been intensively applied for sequential recommender systems nowadays as they take advantage of the self-attention...
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Online Distillation and Preferences Fusion for Graph Convolutional Network-Based Sequential Recommendation
Sequential recommendations make an attempt to predict the next item that a user will interact with based on their historical behavior sequence....
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Self-attention Convolutional Neural Network for Sequential Recommendation
Sequential recommendation uses user-interaction history of preferred items to predict which items a user is most likely to interact with in future....
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Effective and Efficient Transformer Models for Sequential Recommendation
The focus of our work is sequential recommender systems. Sequential recommender systems use ordered sequences of user-item interactions to predict...
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Time Interval Aware Collaborative Sequential Recommendation with Self-supervised Learning
Over the last few years, sequential recommender systems have achieved a great success in different applications. In the literature, it is generally...
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Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision
In Sequential Recommenders (SR), encoding and utilizing modalities in an end-to-end manner is costly in terms of modality encoder sizes. Two-stage...
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Sequential Recommendation Based on Multi-View Graph Neural Networks
The problem of sequential recommendation aims to use a user’s historical interaction sequence to predict and recommend the following item with which...
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A GCN-Based Sequential Recommendation Model for Heterogeneous Information Networks
Sequential recommendation is an important task in the research of recommendation methods for heterogeneous information networks, which is a technique...
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Multi-scale Interest Dynamic Hierarchical Transformer for sequential recommendation
Existing sequential recommendation methods focus on modeling the temporal relationships of users’ historical behaviors and excel in exploiting users’...
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Global-Aware External Attention Deep Model for Sequential Recommendation
The sequential recommender plays a major role in contemporary recommendation systems, which shows the strong ability to model sequential patterns...
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Novel next-group recommendation approach based on sequential market basket information
A market basket is a set of items included in a retail assortment that a customer buys on a shop** trip. The purpose of market basket analysis is...
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Parameters Efficient Fine-Tuning for Long-Tailed Sequential Recommendation
In an era of information explosion, recommendation systems play an important role in people’s daily life by facilitating content exploration. It is...
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Multi-Grained Fusion Graph Neural Networks for Sequential Recommendation
The target of sequential recommendation is to predict the next item that users will interact with according to their historical interaction...
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Conditional Denoising Diffusion for Sequential Recommendation
Contemporary attention-based sequential recommendations often encounter the oversmoothing problem, which generates indistinguishable representations....
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Personalization Through User Attributes for Transformer-Based Sequential Recommendation
Sequential recommendation models are able to learn user preferences based solely on the sequences of past user–item interactions. However, there...
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Leveraging mixed distribution of multi-head attention for sequential recommendation
Attention mechanism has been proven to be a useful model for sequence recommendation. Traditional multi-head self-attention architecture can exploit...
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Multi-pair Contrastive Learning Based on Same-Timestamp Data Augmentation for Sequential Recommendation
The core of sequential recommendations is to model users’ dynamic preferences from their sequential historical behaviors. Bidirectional...
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SSR-MGTI: Self-attention Sequential Recommendation Algorithm Based on Movie Genre Time Interval
As an important part of the recommendation system, movie recommendation system can recommend movies to users accurately according to their...
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Swarm Enhanced Attentive Mechanism for Sequential Recommendation
Recommendation system facilitates users promptly obtaining the information they need in this age of data explosion. Research on recommendation models...