Sequential recommendation (SR) aims to model user preferences by capturi...
Sequential recommendation aims to capture users' dynamic interest and
pr...
Deep learning and symbolic learning are two frequently employed methods ...
The self-attention mechanism, which equips with a strong capability of
m...
Although recent network representation learning (NRL) works in
text-attr...
Many machine learning algorithms have been developed in recent years to
...
In order to deal with variant-length long videos, prior works extract
mu...
Contrastive learning with Transformer-based sequence encoder has gained
...
Knowledge distillation in machine learning is the process of transferrin...
Sequential Recommendation aims to predict the next item based on user
be...
Sequential recommendation has been a widely popular topic of recommender...
Graph Convolution Network (GCN) has been widely applied in recommender
s...
In our daily life, the scenes around us are always with multiple labels
...
Distributed Denial of Service (DDoS) attack has become one of the most
d...
When purchasing appearance-first products, e.g., clothes, product appear...
Distributed denial of service (DDoS) attacks have caused huge economic l...
Next Point-of-Interest (POI) recommendation is of great value for both
l...