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ORCID27th PAKDD 2023: Osaka, Japan - Part III
- Hisashi Kashima
, Tsuyoshi Idé, Wen-Chih Peng:
Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III. Lecture Notes in Computer Science 13937, Springer 2023, ISBN 978-3-031-33379-8
Big Data
- Haiyang Xia, Qian Li, Zhichao Wang, Gang Li:
Toward Explainable Recommendation via Counterfactual Reasoning. 3-15 - Yuchen Zhang, Mingjun Zhao, Chenglin Li, Weiyu Tou, Haolan Chen, Di Niu, Cunxiang Yin, Yancheng He, Fei Guo:
Online Volume Optimization for Notifications via Long Short-Term Value Modeling. 16-28 - Palla Likhitha, Pamalla Veena, Rage Uday Kiran, Koji Zettsu:
Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases. 29-41
Financial Data
- Lili Wang, Chenghan Huang, Chongyang Gao, Weicheng Ma, Soroush Vosoughi:
Joint Latent Topic Discovery and Expectation Modeling for Financial Markets. 45-57 - Sarmistha Das, Apoorva Singh, Raghav Jain, Sriparna Saha, Alka Maurya:
Let the Model Make Financial Senses: A Text2Text Generative Approach for Financial Complaint Identification. 58-69
Information Retrieval and Search
- Aashiq Muhamed, Sriram Srinivasan, Choon Hui Teo, Qingjun Cui, Belinda Zeng, Trishul Chilimbi, S. V. N. Vishwanathan:
Web-Scale Semantic Product Search with Large Language Models. 73-85 - Mengmeng Kuang, Zhenhong Chen, Weiyan Wang, Lie Kang, Qiang Yang, Min Tang, Penghui Hao:
Multi-task Learning Based Keywords Weighted Siamese Model for Semantic Retrieval. 86-98 - Qiao Qiao, Yuepei Li, Kang Zhou, Qi Li:
Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion. 99-111 - Debopriyo Banerjee, Mausam Jain, Ashish Kulkarni:
MFBE: Leveraging Multi-field Information of FAQs for Efficient Dense Retrieval. 112-124 - Euna Jung, Jungwon Park, Jaekeol Choi, Sungyoon Kim, Wonjong Rhee:
Isotropic Representation Can Improve Dense Retrieval. 125-137 - Yanhu Li, Taolin Zhang, Dongyang Li, Xiaofeng He:
Knowledge-Enhanced Prototypical Network with Structural Semantics for Few-Shot Relation Classification. 138-149
Internet of Things
- Qiaochuan Chen, Min Zhou, Hang Yu:
MIDFA: Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection. 153-164
Medical and Biological Data
- Neel Kanwal, Trygve Eftestøl, Farbod Khoraminia, Tahlita C. M. Zuiverloon, Kjersti Engan:
Vision Transformers for Small Histological Datasets Learned Through Knowledge Distillation. 167-179 - Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rügamer:
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis. 180-191 - Yankai Tian, Yijia Zhang, Xingwang Li, Mingyu Lu:
DKFM: Dual Knowledge-Guided Fusion Model for Drug Recommendation. 192-203 - Quan Li, Lingwei Chen, Yong Cai, Dinghao Wu:
Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge. 204-215
Multimedia and Multimodal Data
- David Hason Rudd, Huan Huo, Guandong Xu:
An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance. 219-231 - Tomer Friedlander, Lior Wolf:
Dynamically-Scaled Deep Canonical Correlation Analysis. 232-244 - Yakun Yu, Jiuding Yang, Weidong Guo, Hui Liu, Yu Xu, Di Niu:
TCR: Short Video Title Generation and Cover Selection with Attention Refinement. 245-256 - Zhen Liu, Yongxin Zhu, Zhujin Gao, Xin Sheng, Linli Xu:
ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval. 257-268
Recommender Systems
- Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa:
Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations. 271-283 - Huachi Zhou, Shuang Zhou, Keyu Duan, Xiao Huang, Qiaoyu Tan, Zailiang Yu:
Interest Driven Graph Structure Learning for Session-Based Recommendation. 284-296 - Weijun Xu, Han Li, Meihong Wang:
Multi-behavior Guided Temporal Graph Attention Network for Recommendation. 297-309 - Edoardo D'Amico, Aonghus Lawlor, Neil Hurley:
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. 310-321 - Jinze Wang, Lu Zhang, Zhu Sun, Yew-Soon Ong:
Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities. 322-334 - Tianxing Wang, Can Wang:
Global-Aware External Attention Deep Model for Sequential Recommendation. 335-347 - Hyunsik Jeon, Jongjin Kim, Jaeri Lee, Jong-eun Lee, U Kang:
Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-Aware Reranking. 348-360 - Jongjin Kim, Hyunsik Jeon, Jaeri Lee, U Kang:
Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation. 361-373 - Ahmed El-Kishky, Thomas Markovich, Kenny Leung, Frank Portman, Aria Haghighi, Ying Xiao:
bfkNN-Embed: Locally Smoothed Embedding Mixtures for Multi-interest Candidate Retrieval. 374-386 - Zhaoqi Yang, Hongyan Liu:
Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation. 387-399 - Jing Wang, Mengchen Zhao, Wei Xia, Zhenhua Dong, Ruiming Tang, Rui Zhang, Jianye Hao, Guangyong Chen, Pheng-Ann Heng:
RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling. 400-413
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