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ORCID29th DASFAA 2024: Gifu, Japan - Part VI
- 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 VI. Lecture Notes in Computer Science 14855, Springer 2024, ISBN 978-981-97-5571-4
Graph and Network
- Nan Liu, Shunmei Meng, Yu Jiang, Qianmu Li, Xiaolong Xu, Lianyong Qi, Xuyun Zhang:
Cascading Graph Convolution Contrastive Learning Networks for Multi-behavior Recommendation. 3-18 - Jiaxi Wang, Bingce Wang, Liwen Zhang, Tong Mo, Weiping Li:
Social Relation Enhanced Heterogeneous Graph Contrastive Learning for Recommendation. 19-34 - ZhenZhong Zheng, Jianxin Li, Xiaoming Wu, Xiangzhi Liu, Lili Pei:
Higher-Order Graph Contrastive Learning for Recommendation. 35-51 - Herun Wan, Ningnan Wang, Xiang Zhao, Rui Li, Hui Yang, Minnan Luo:
FNDPro: Evaluating the Importance of Propagations during Fake News Spread. 52-67 - Bradley Ashmore, Lingwei Chen:
Leveraging Homophily-Augmented Energy Propagation for Bot Detection on Graphs. 68-83 - Zihan Feng, Rui Wu, Yajun Yang, Hong Gao, Xin Wang, Xueli Liu, Qinghua Hu:
Multi-level Contrastive Learning on Weak Social Networks for Information Diffusion Prediction. 84-100 - Chunkai Zhang, Guoqing Li:
BiasRec: A General Bias-Aware Social Recommendation Model. 101-116 - Yucheng Jin, Yun Xiong, Juncheng Fang, Xixi Wu, Dongxiao He, Xing Jia, Bingchen Zhao, Philip S. Yu:
Beyond the Known: Novel Class Discovery for Open-World Graph Learning. 117-133 - Jiakai Tang, Zuxu Sun, Wei Yao, Xu Chen:
Robust Graph Recommendation via Noise-Aware Adversarial Perturbation. 134-150 - Nian Liu, Shen Fan, Ting Bai, Peng Wang, Mingwei Sun, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Chuan Shi:
Learning Social Graph for Inactive User Recommendation. 151-167 - Jingya Zhou:
MANE: A Multi-cascade Adversarial Network Embedding Model for Anchor Link Prediction. 168-184 - Nuo Li, Bin Guo, Yao Jing, Zhiwen Yu:
uTransfer: Unified Transferability Metric Incorporating Heterogeneous User Data in Social Network. 185-202 - Cheng Li, Pei-Yuan Lai, Yi-Hong Lu, De-Zhang Liao, Xiao-Dong Huang, Chang-Dong Wang:
GPSR: Graph Prompt for Session-Based Recommendation. 203-219 - Yuexian Wang, Wenze Ma, Yanmin Zhu, Chunyang Wang, Zhaobo Wang, Feilong Tang, Jiadi Yu:
Guiding Graph Learning with Denoised Modality for Multi-modal Recommendation. 220-235 - Qingcheng Lu, Nannan Wu, Yiming Zhao, Wenjun Wang, Quannan Zu:
Enhancing Multi-view Contrastive Learning for Graph Anomaly Detection. 236-251 - JiaJia Li, Yannan Wang, Rui Zhu, Jing Zhang, Na Guo:
Global Route Planning for Large-Scale Requests on Traffic-Aware Road Network. 252-268 - Zehao Guo, Nannan Wu, Yiming Zhao, Wenjun Wang:
TransGAD: A Transformer-Based Autoencoder for Graph Anomaly Detection. 269-284 - Hang Cui, Tarek F. Abdelzaher:
Unsupervised Node Clustering via Contrastive Hard Sampling. 285-300 - Zihao Liu, Yitong Wang:
DySDGNN: Representation Learning in Dynamic Signed Directed Networks. 301-310 - Yibowen Zhao, Yonghui Xu, Yixin Zhang, Wei He, Lizhen Cui:
Multi-objective Graph Neural Network Explanatory Model with Local and Global Information Preservation. 311-320 - Hewen Wang, Bryan Hooi, Dan He, Juncheng Liu, Xiaokui Xiao:
EGNN-AD: An Effective Graph Neural Network-Based Approach for Anomaly Detection on Edge-Attributed Graphs. 321-331 - Qi Dai, Yumeng Song, Yu Gu, Fangfang Li, Xiaohua Li:
Diffusion Model-Enhanced Contrastive Learning for Graph Representation. 332-341 - Shixiong Jing, Lingwei Chen, Quan Li, Dinghao Wu:
H2GNN: Graph Neural Networks with Homophilic and Heterophilic Feature Aggregations. 342-352 - Shasha Hu, Chao Wang, Chuan Qin, Hengshu Zhu, Hui Xiong:
Super-Node Generation for GNN-Based Recommender Systems: Enhancing Distant Node Integration via Graph Coarsening. 353-363 - Yang Li, Bingbing Xu, Fei Sun, Qi Cao, Yige Yuan, Huawei Shen, Xueqi Cheng:
History Driven Sampling for Scalable Graph Neural Networks. 364-374 - Yao Zou, Sheng Xiang, Qijun Miao, Dawei Cheng, Changjun Jiang:
Subgraph Patterns Enhanced Graph Neural Network for Fraud Detection. 375-384 - Yulan Hu, Ge Chen, Sheng Ouyang, Zhirui Yang, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Zhao Cao, Shangquan Wu, Yong Liu:
Advancing Latent Representation Ranking for Masked Graph Autoencoder. 385-394 - Yuechen Tang, Huifang Ma, Ke Shu, Zhixin Li, Liang Chang:
Path-Aware Co-contrastive Learning for Signed Directed Network Embedding. 395-406 - Yuxuan Bian, Haoyu Sun, Yang Lei, Peng Zhu, Dawei Cheng:
NGDRL: A Dynamic News Graph-Based Deep Reinforcement Learning Framework for Portfolio Optimization. 407-417 - Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang:
CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. 418-428 - Kyusik Kim, Bongwon Suh:
SymphoNEI: Symphony of Node and Edge Inductive Representations on Large Heterophilic Graphs. 429-439 - Kyusik Kim, Bongwon Suh:
HopLearn: Leveraging Multi-Hop Neighbors and Learnable Parameters for GNNs with Missing Node Features. 440-450
Hardware Acceleration
- Congyong Chen, Shengan Zheng, Yuhang Zhang, Linpeng Huang:
Redesigning Data and Metadata Updates in PM File Systems with Persistent CPU Caches. 453-462 - Ke Han, Wen Cheng, Yong Li, Yunxiang Wu, Lingfang Zeng, Guang Chen:
Reusing Your Prepared Data: An Informed Cache for Accelerating DNN Model Training. 463-473 - Rongrong Zhang, Zhiwei Ye, Peng Cai, Xuan Zhou, Aoying Zhou, Dunbo Cai, Ling Qian:
HyBuffer: A Distributed Hybrid Shared Buffer for Multi-master Databases. 474-483
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