default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID29th DASFAA 2024: Gifu, Japan - Part III
- Makoto Onizuka
, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu:
Database Systems for Advanced Applications - 29th International Conference, DASFAA 2024, Gifu, Japan, July 2-5, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14852, Springer 2025, ISBN 978-981-97-5554-7
Recommendation
- Weiyang Guo, Yue Cui, Kai Zheng:
IntFair:Graph Neural Networks for Fair Recommendations with Interest Awareness. 3-18 - Jingya Zhou, Jie Wang:
A Novel Multi-Task driven Model for Personalized Paper Recommendations. 19-34 - Xinyue Liu, Bohan Li, Yijun Chen, Xiaoxue Li, Shuai Xu, Hongzhi Yin:
Disentangled Representations for Cross-Domain Recommendation via Heterogeneous Graph Contrastive Learning. 35-50 - Yiyuan Zheng, Beihong Jin, Beibei Li, Weijiang Lai, Tao Xiang:
Reducing Interaction Noise for Sequential Recommendation via Robust Interests. 51-66 - Hangtong Xu, Yuanbo Xu, Yongjian Yang:
Separating and Learning Latent Confounders to Enhancing User Preferences Modeling. 67-82 - Tongyu Wu, Jianfeng Qu, Deqing Wang, Zhiming Cui, Guanfeng Liu, Pengpeng Zhao:
Contrasting Transformer and Hypergraph Network for Cooperative Sequential Recommendation. 83-98 - Jiayu Li, Peijie Sun, Chumeng Jiang, Weizhi Ma, Qingyao Ai, Min Zhang:
A Situation-aware Enhancer for Personalized Recommendation. 99-114 - Luankang Zhang, Hao Wang, Suojuan Zhang, Mingjia Yin, Yongqiang Han, Jiaqing Zhang, Defu Lian, Enhong Chen:
A Unified Framework for Adaptive Representation Enhancement and Inversed Learning in Cross-Domain Recommendation. 115-130 - Ming He, Chang Liu, Han Zhang, Zihao Zhang:
Causal Disentangled Sentiment Debiasing for Recommendation. 131-147 - Yabin Zhang, Jiakai Tang, Xu Chen:
Alleviating Dimensional Collapse Problem in Deep Recommender Models by Designing Uniformity Layers. 148-163 - Sirui Huang, Qian Li, Xiangmeng Wang, Dianer Yu, Guandong Xu, Qing Li:
Counterfactual Debasing for Multi-behavior Recommendations. 164-179 - Meng Yan, Haibin Huang, Ying Liu, Juan Zhao, Xiyue Gao, Cai Xu, Ziyu Guan, Wei Zhao:
TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal Content. 180-195 - Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li:
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness. 196-211 - Zhaoxiang Zhang, Zhiheng Li, Jipeng Jin, Xiaofeng Gao, Xiongwen Yang, Bo Zhang, Lei Xiao:
DeepMIN: Deep Multi-modal Interest Network with Cognitive Learning Modules. 212-227 - Boci Peng, Xiaohe Bo, Jiayan Guo, Yan Zhang:
A Diffusion Model with User Preference Guidance for Recommendation. 228-244 - Zhuhang Li, Ning Yang:
Cross-Domain Causal Preference Learning for Out-of-Distribution Recommendation. 245-260 - Guixin Chu, Xinye Guan, Yiran Shi, Bangzuo Zhang, Dongbing Pu:
Self-augmented Contrastive Learning for Knowledge-Aware Recommendation. 261-276 - Siying Chen, Xiaoou Ding, Zheng Liang, Yafeng Tang, Hongzhi Wang:
Hyper-parameter Recommendation for Truth Discovery. 277-292 - Jiakai Tang, Xueyang Feng, Xu Chen:
Fairness-aware Cross-Domain Recommendation. 293-302 - Aoran Zhang, Yonghong Yu, Gongyou Xu, Rong Gao, Li Zhang, Shang Gao, Hongzhi Yin:
Hyperbolic Adversarial Learning for Personalized Item Recommendation. 303-312 - Yao Xiao, Jin Liu, Guangyou Zhou:
Heterogeneous Hypergraph Polynomial Learning for Herb Recommendation. 313-322 - Xun Cai, Yuxiang Lu, Hongtao Lu, Yue Ding:
Towards Mixture of Task-Intensive Experts for Multi-task Recommendation. 323-332 - Zhiying Deng, Jianjun Li, Li Zou, Wei Liu, Si Shi, Qian Chen, Juan Zhao, Guohui Li:
Multi-scale Context-aware User Interest Learning for Behavior Pattern Modeling. 333-342 - Yang Li, Qi'ao Zhao, Chen Lin, Zhenjie Zhang, Xiaomin Zhu, Jinsong Su:
GENET: Unleashing the Power of Side Information for Recommendation via Hypergraph Pre-training. 343-352 - Junzhe Jiang, Shang Qu, Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Kai Zhang, Rui Li, Jiatong Li, Min Gao:
Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling. 353-362 - Hao Zhang, Mingyue Cheng, Qi Liu, Yucong Luo, Rui Li, Enhong Chen:
Learning Recommender Systems with Soft Target: A Decoupled Perspective. 363-373 - Xiaoxue Li, Bohan Li, Yijun Chen, Xinyue Liu, Shuai Xu, Meng Wang:
Next POI Recommendation based on Adaptive Graph Learning and Future Preferences. 374-384
Multi-media
- Dong Zhang, Wenjie Lu, Shoushan Li, Guodong Zhou:
Bilingual Multimodal Graph Modeling for Text-Image Relation Inference. 387-402 - Zhiyuan Liu, Yirui Ma, Wei Chen, Qian Zhou, Lei Zhao:
HMM: A Hybrid Multi-modal Model for User Identity Linkage. 403-418 - Haoyu Liu, Yaoxian Song, Xuwu Wang, Xiangru Zhu, Zhixu Li, Wei Song, Tiefeng Li:
Flickr30K-CFQ: A Compact and Fragmented Query Dataset for Text-image Retrieval. 419-434 - Xueyang Li, Haotian Chen, Yunzhong Lou, Xiangdong Zhou:
CF-CAD: A Contrastive Fusion Network For 3D Computer-Aided Design Generative Modeling. 435-450 - Shiqiang Ma, Fei Guo, Jijun Tang:
SiamSegNet: A multimodal Segmentation Method Based on Cross-modal Generation for Medical Image Segmentation. 451-466 - Xiaolong She, Jingya Zhou, Zhenyu Hu, Boyu Du:
Cross-view Contrastive Learning Enhanced Heterogeneous Graph Networks for Multi-modal Recipe Recommendation. 467-482 - Yan Kang, Hao Lin, Mingjian Yang, Shin-Jye Lee:
UMAIR-FPS: User-aware Multi-modal Animation Illustration Recommendation Fusion with Painting Style. 483-494 - Minju Kim, Seonggyeom Kim, Dong-Kyu Chae:
Unsupervised Controllable Generation of Diffusion Models with Latent Variables in VAEs. 495-504
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-02-21 19:39 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
