ACM International Conference on Knowledge Discovery and Data Mining

KDD

CORE rank

CORE rank (raw)

Acceptance rate

20.0% (2024 research track)

Fields of research

Data Management and Data Science · Machine Learning

Papers indexed

8,232

1994–2026

Best Machine Learning conferences Best Data Science and Information Retrieval conferences

Papers per year

1994844 peak2026

Most published authors

KDD papers

8,232 records sourced from DBLP. Search titles, filter by year, sort by recency.

Year	Title	Authors
2023	SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding.	Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky
2023	Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting.	Ergute Bao, Dawei Gao, Xiaokui Xiao, Yaliang Li
2023	Knowledge Graph Reasoning over Entities and Numerical Values.	Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song
2023	AdKDD 2023.	Abraham Bagherjeiran, Nemanja Djuric, Kuang-Chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan
2023	Rank-heterogeneous Preference Models for School Choice.	Amel Awadelkarim, Arjun Seshadri, Itai Ashlagi, Irene Lo, Johan Ugander
2023	Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents.	Yash Kumar Atri, Vikram Goyal, Tanmoy Chakraborty
2023	Learning to Solve Grouped 2D Bin Packing Problems in the Manufacturing Industry.	Wenxuan Ao, Guozhen Zhang, Yong Li, Depeng Jin
2023	CADENCE: Offline Category Constrained and Diverse Query Generation for E-commerce Autosuggest.	Abhinav Anand, Surender Kumar, Nandeesh Kumar, Samir Shah
2023	NFT-Based Data Marketplace with Digital Watermarking.	Saeed Ranjbar Alvar, Mohammad Akbari, David (Ming Xuan) Yue, Yong Zhang
2023	LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias.	Mario Almagro, Emilio J. Almazn, Diego Ortego, David Jimnez
2023	Fair Allocation Over Time, with Applications to Content Moderation.	Amine Allouah, Christian Kroer, Xuan Zhang, Vashist Avadhanula, Nona Bohanon, Anil Dania, Caner Gocmen, Sergey Pupyrev, Parikshit Shah, Nicols Stier Moses, Ken Rodrguez Taarup
2023	KDD Workshop on Machine Learning in Finance.	Leman Akoglu, Nitesh V. Chawla, Senthil Kumar, Saurabh Nagrecha, Mahashweta Das, Vidyut M. Naware, Tanveer A. Faruquie
2023	Maximizing Neutrality in News Ordering.	Rishi Advani, Paolo Papotti, Abolfazl Asudeh
2023	Minimizing Hitting Time between Disparate Groups with Shortcut Edges.	Florian Adriaens, Honglian Wang, Aristides Gionis
2023	epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.	Bijaya Adhikari, Alexander Rodrguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash
2023	Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond.	Naoki Abe, Kathleen Buckingham, Yuzhou Chen, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, Yulia R. Gel, James Hodson, Ramakrishnan Kannan, Huikyo Lee, Jiafu Mao, Rose Yu
2023	Exploiting Intent Evolution in E-commercial Query Recommendation.	Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Xiao Cheng, Bing Yin, Suhang Wang, Philip S. Yu
2023	Meta Multi-agent Exercise Recommendation: A Game Application Perspective.	Fei Liu, Xuegang Hu, Shuochen Liu, Chenyang Bu, Le Wu
2023	Quantifying Node Importance over Network Structural Stability.	Fan Zhang, Qingyuan Linghu, Jiadong Xie, Kai Wang, Xuemin Lin, Wenjie Zhang
2023	Towards Variance Reduction for Reinforcement Learning of Industrial Decision-making Tasks: A Bi-Critic based Demand-Constraint Decoupling Approach.	Jianyong Yuan, Jiayi Zhang, Zinuo Cai, Junchi Yan
2023	Spatio-temporal Diffusion Point Processes.	Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, Yong Li
2023	Generative Causal Interpretation Model for Spatio-Temporal Representation Learning.	Yu Zhao, Pan Deng, Junting Liu, Xiaofeng Jia, Jianwei Zhang
2023	Personalized Federated Learning with Parameter Propagation.	Jun Wu, Wenxuan Bao, Elizabeth A. Ainsworth, Jingrui He
2023	Metric@CustomerN: Evaluating Metrics at a Customer Level in E-Commerce.	Mayank Singh, Emily Ray, Marc Ferradou, Andrea Barraza-Urbina
2023	Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation.	Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

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