Titlebook: Knowledge Science, Engineering and Management; 16th International C Zhi Jin,Yuncheng Jiang,Wenjun Ma Conference proceedings 2023 The Editor

昆蟲(chóng)

施魔法

顯而易見(jiàn)

Hypergraph Enhanced Contrastive Learning for?News Recommendation a fine-grained topic level and encodes useful information into the representations of users and items. Meanwhile, the designed hypergraph structure learning module enhances the discrimination ability and enriches the complex high-order dependencies, which improves the presentation quality of the re

tackle

A Session Recommendation Model Based on Heterogeneous Graph Neural Networkeature representations, and the attention mechanism weights the features according to each user’s current interests. We evaluate our method on two public datasets, and our results show that our model outperforms existing approaches in terms of accuracy and robustness. In conclusion, our proposed met

甜得發(fā)膩

刺穿

cloture

CoMeta: Enhancing Meta Embeddings with?Collaborative Information in?Cold-Start Problem of?Recommendags of old items as its base embedding; S-EG generates its shift embedding not only with its attribute features but also with the average ID embedding of the users who interacted with it. The final meta embedding is obtained by adding up the base embedding and the shift embedding. We conduct extensiv

Malleable

A Graph Neural Network for Cross-domain Recommendation Based on Transfer and Inter-domain Contrastive transfer. Finally, contrastive learning is performed on the overlapping users or items in the two domains, and the self-supervised contrastive learning task and supervised learning task are jointly trained to alleviate the differences between the two domain.

FILTH

Moming Tang,Chengyu Wang,Jianing Wang,Cen Chen,Ming Gao,Weining Qianort verschiedene Projekte im Bereich der Gesundheits?konomie und Versorgungsforschung. Die Arbeit entstand als Dissertation an der Universit?t Greifswald, an de978-3-658-32542-8978-3-658-32543-5Series ISSN 2523-7667 Series E-ISSN 2523-7675

勛章

Chao Chang,Junming Zhou,Weisheng Li,Zhengyang Wu,Jing Gao,Yong Tang