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ORCID27th DASFAA 2022: Virtual Event - Part II
- Arnab Bhattacharya, Janice Lee, Mong Li, Divyakant Agrawal, P. Krishna Reddy
, Mukesh K. Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran:
Database Systems for Advanced Applications - 27th International Conference, DASFAA 2022, Virtual Event, April 11-14, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13246, Springer 2022, ISBN 978-3-031-00125-3
Recommendation Systems
- Haolin Zhou, Qingmin Liu, Xiaofeng Gao, Guihai Chen:
MDKE: Multi-level Disentangled Knowledge-Based Embedding for Recommender Systems. 3-18 - Yingpeng Du, Hongzhi Liu, Zhonghai Wu:
M3-IB: A Memory-Augment Multi-modal Information Bottleneck Model for Next-Item Recommendation. 19-35 - Xingyu Zhang, Chaofeng Sha:
Fully Utilizing Neighbors for Session-Based Recommendation with Graph Neural Networks. 36-52 - Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang, Kuan Liu:
Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation. 53-68 - Xuan Ma, Tieyun Qian, Yile Liang, Ke Sun, Hang Yun, Mi Zhang:
Enhancing Graph Convolution Network for Novel Recommendation. 69-84 - Qimin Ban, Wen Wu, Wenxin Hu, Hui Lin, Wei Zheng, Liang He:
Knowledge-Enhanced Multi-task Learning for Course Recommendation. 85-101 - Ting Bai, Yanlong Huang, Bin Wu:
Learning Social Influence from Network Structure for Recommender Systems. 102-117 - Liye Shi, Wen Wu, Yu Ji, Luping Feng, Liang He:
PMAR: Multi-aspect Recommendation Based on Psychological Gap. 118-133 - Hang Miao, Anchen Li, Bo Yang:
Meta-path Enhanced Lightweight Graph Neural Network for Social Recommendation. 134-149 - Chuan Cui, Qi Shen, Shixuan Zhu, Yitong Pang, Yiming Zhang, Hanning Gao, Zhihua Wei:
Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation. 150-165 - Yiqing Wu, Ruobing Xie, Yongchun Zhu, Xiang Ao, Xin Chen, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Qing He:
Multi-view Multi-behavior Contrastive Learning in Recommendation. 166-182 - Zhiqiang Guo, Chaoyang Wang, Zhi Li, Jianjun Li, Guohui Li:
Joint Locality Preservation and Adaptive Combination for Graph Collaborative Filtering. 183-198 - Tianchi Yang, Luhao Zhang, Chuan Shi, Cheng Yang, Siyong Xu, Ruiyu Fang, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang:
Gated Hypergraph Neural Network for Scene-Aware Recommendation. 199-215 - Weibin Zhao, Aoran Zhang, Lin Shang, Yonghong Yu, Li Zhang, Can Wang, Jiajun Chen, Hongzhi Yin:
Hyperbolic Personalized Tag Recommendation. 216-231 - Lingzi Zhang, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, Haihong Tang:
Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback. 232-247 - Yunhe Wei, Huifang Ma, Yike Wang, Zhixin Li, Liang Chang:
Multi-behavior Recommendation with Two-Level Graph Attentional Networks. 248-255 - Longcan Wu, Daling Wang, Shi Feng, Kaisong Song, Yifei Zhang, Ge Yu:
Collaborative Filtering for Recommendation in Geometric Algebra. 256-263 - Junfa Lin, Siyuan Chen, Jiahai Wang:
Graph Neural Networks with Dynamic and Static Representations for Social Recommendation. 264-271 - Jie Wang, Jinya Zhou, Zhen Wu, Xigang Sun:
Toward Paper Recommendation by Jointly Exploiting Diversity and Dynamics in Heterogeneous Information Networks. 272-280 - Xiaohui Zhang, Huifang Ma, Zihao Gao, Zhixin Li, Liang Chang:
Enhancing Session-Based Recommendation with Global Context Information and Knowledge Graph. 281-288 - Yalei Zang, Yi Liu, Weitong Chen, Bohan Li, Aoran Li, Lin Yue, Weihua Ma:
GISDCN: A Graph-Based Interpolation Sequential Recommender with Deformable Convolutional Network. 289-297 - Yifan Wang, Yongkang Li, Shuai Li, Weiping Song, Jiangke Fan, Shan Gao, Ling Ma, Bing Cheng, Xunliang Cai, Sheng Wang, Ming Zhang:
Deep Graph Mutual Learning for Cross-domain Recommendation. 298-305 - Zhengyang Ai, Shupeng Wang, Siyu Jia, Shu Guo:
Core Interests Focused Self-attention for Sequential Recommendation. 306-314 - Xiaoning Zong, Yong Liu, Yonghui Xu, Yixin Zhang, Zhiqi Shen, Yonghua Yang, Lizhen Cui:
SAER: Sentiment-Opinion Alignment Explainable Recommendation. 315-322 - Bo Sun, Di Wu, Mingsheng Shang, Yi He:
Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems. 323-331 - Chengming Zou, Zhenfeng Fan:
GELibRec: Third-Party Libraries Recommendation Using Graph Neural Network. 332-340
Applications of Machine Learning
- Lianjie Long, Yunfei Yin, Faliang Huang:
Hierarchical Attention Factorization Machine for CTR Prediction. 343-358 - Fangye Wang, Hansu Gu, Dongsheng Li, Tun Lu, Peng Zhang, Ning Gu:
MCRF: Enhancing CTR Prediction Models via Multi-channel Feature Refinement Framework. 359-374 - Yijiang Chen, Xiangdong Zhou, Zhen Xing, Zhidan Liu, Minyang Xu:
CaSS: A Channel-Aware Self-supervised Representation Learning Framework for Multivariate Time Series Classification. 375-390 - Xiuting Song, Luyi Bai, Rongke Liu, Han Zhang:
Temporal Knowledge Graph Entity Alignment via Representation Learning. 391-406 - Fuqiang Yu, Lizhen Cui, Yiming Cao, Ning Liu, Weiming Huang, Yonghui Xu:
Similarity-Aware Collaborative Learning for Patient Outcome Prediction. 407-422 - Cong Zhang, Ting Bai, Bin Wu:
Semi-supervised Graph Learning with Few Labeled Nodes. 423-438 - Tao Sun, Fei Wang, Zhao Zhang, Lin Wu, Yongjun Xu:
Human Mobility Identification by Deep Behavior Relevant Location Representation. 439-454 - Shenglai Zeng, Zonghang Li, Hongfang Yu, Yihong He, Zenglin Xu, Dusit Niyato, Han Yu:
Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training. 455-471 - Yu Fan, Jiajie Xu, Rui Zhou, Chengfei Liu:
Transportation-Mode Aware Travel Time Estimation via Meta-learning. 472-488 - Bing Shi, Zhi Cao, Yikai Luo:
A Deep Reinforcement Learning Based Dynamic Pricing Algorithm in Ride-Hailing. 489-505 - Weixian Zong, Fang Zhou, Martin Pavlovski, Weining Qian:
Peripheral Instance Augmentation for End-to-End Anomaly Detection Using Weighted Adversarial Learning. 506-522 - Shi Wang, Daniel Tang, Luchen Zhang, Huilin Li, Ding Han:
HieNet: Bidirectional Hierarchy Framework for Automated ICD Coding. 523-539 - Mingming Zhang, Peng Wang, Wei Wang:
Efficient Consensus Motif Discovery of All Lengths in Multiple Time Series. 540-555 - Geping Yang, Sucheng Deng, Yiyang Yang, Zhiguo Gong, Xiang Chen, Zhifeng Hao:
LiteWSC: A Lightweight Framework for Web-Scale Spectral Clustering. 556-573 - Junwei Lv, Ying He, Xuegang Hu, Desheng Cai, Yuqi Chu, Jun Hu:
Dual Confidence Learning Network for Open-World Time Series Classification. 574-589 - Jingze Li, Shengmin Shi, Tongbing Chen, Yu Tian, Yihua Ding, Yiyong Xiao, Weiwei Sun:
Port Container Throughput Prediction Based on Variational AutoEncoder. 590-605 - Ruisheng Zhang, Yansheng Wang, Zimu Zhou, Ziyao Ren, Yongxin Tong, Ke Xu:
Data Source Selection in Federated Learning: A Submodular Optimization Approach. 606-614 - Yuanning Gao, Xiaofeng Gao, Guihai Chen:
MetisRL: A Reinforcement Learning Approach for Dynamic Routing in Data Center Networks. 615-622 - Kun Li, Meng Lin, Songlin Hu, Ruixuan Li:
CLZT: A Contrastive Learning Based Framework for Zero-Shot Text Classification. 623-630 - Xinyu Ma, Meng Wang, Xing Liu, Yifan Yang, Yefeng Zheng, Sen Wang:
InDISP: An Interpretable Model for Dynamic Illness Severity Prediction. 631-638 - Junming Shao, Kai Wang, Jianyun Lu, Zhili Qin, Qiming Wangyang, Qinli Yang:
Learning Evolving Concepts with Online Class Posterior Probability. 639-647 - Bolei Zhang, Fu Xiao:
Robust Dynamic Pricing in Online Markets with Reinforcement Learning. 648-655 - Zhewen Duan, Xiuwen Yi, Peng Li, Dekang Qi, Yexin Li, Haoran Xu, Yanyong Huang, Junbo Zhang, Yu Zheng:
Multi-memory Enhanced Separation Network for Indoor Temperature Prediction. 656-663 - Fan Qiao, Peng Wang, Wei Wang, Binjie Wang:
An Interpretable Time Series Classification Approach Based on Feature Clustering. 664-672 - Qi Wang, Suzanne V. Blackley, Chunlei Tang:
Generative Adversarial Imitation Learning to Search in Branch-and-Bound Algorithms. 673-680 - Yan Chen, Lei Wang, Liang Du, Lei Duan:
A Trace Ratio Maximization Method for Parameter Free Multiple Kernel Clustering. 681-688 - Xiaoyang Li, Martin Pavlovski, Fang Zhou, Qiwen Dong, Weining Qian, Zoran Obradovic:
Supervised Multi-view Latent Space Learning by Jointly Preserving Similarities Across Views and Samples. 689-696 - Bin Fu, Hongzhi Liu, Hui Zhao, Yao Zhu, Yang Song, Tao Zhang, Zhonghai Wu:
Market-Aware Dynamic Person-Job Fit with Hierarchical Reinforcement Learning. 697-705 - Xiuqi Huang, Yunlong Cheng, Xiaofeng Gao, Guihai Chen:
TEALED: A Multi-Step Workload Forecasting Approach Using Time-Sensitive EMD and Auto LSTM Encoder-Decoder. 706-713
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