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
2019	Building a Knowledge Graph for Recommending Experts.	Behnam Rahdari, Peter Brusilovsky
2019	DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview.	Chuan Qin, Hengshu Zhu, Chen Zhu, Tong Xu, Fuzhen Zhuang, Chao Ma, Jingshuai Zhang, Hui Xiong
2019	Deep Reinforcement Learning with Applications in Transportation.	Zhiwei (Tony) Qin, Jian Tang, Jieping Ye
2019	Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.	Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai
2019	Hypothesis Testing and Statistically-sound Pattern Mining.	Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
2019	SPuManTE: Significant Pattern Mining with Unconditional Testing.	Leonardo Pellegrina, Matteo Riondato, Fabio Vandin
2019	Mining Graphs and Networks: A 15-Year Journey.	Jian Pei
2019	TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank.	Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf
2019	Learning Sleep Quality from Daily Logs.	Sungkyu Park, Cheng-Te Li, Sungwon Han, Cheng Hsu, Sang Won Lee, Meeyoung Cha
2019	Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks.	Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos
2019	Estimating Graphlet Statistics via Lifting.	Kirill Paramonov, Dmitry Shemetov, James Sharpnack
2019	Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising.	Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, Aaron Flores
2019	Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning.	Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang
2019	Deep Anomaly Detection with Deviation Networks.	Guansong Pang, Chunhua Shen, Anton van den Hengel
2019	TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme.	Zheyi Pan, Jie Bao, Weinan Zhang, Yong Yu, Yu Zheng
2019	Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction.	Wentao Ouyang, Xiuwu Zhang, Li Li, Heng Zou, Xin Xing, Zhaojie Liu, Yanlong Du
2019	Towards Learning from User Feedback for Ontology-based Information Extraction.	Kobkaew Opasjumruskit, Sirko Schindler, Laura Thiele, Philipp Matthias Schfer
2019	Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones.	Tadashi Okoshi, Kota Tsubouchi, Hideyuki Tokuda
2019	Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information.	Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda
2019	Sequential Anomaly Detection using Inverse Reinforcement Learning.	Min-hwan Oh, Garud Iyengar
2019	Real-time On-Device Troubleshooting Recommendation for Smartphones.	Keiichi Ochiai, Kohei Senkawa, Naoki Yamamoto, Yuya Tanaka, Yusuke Fukazawa
2019	Knowledge Graph Completion with FAMER (DI2KG Challenge Winner).	Daniel Obraczka, Alieh Saeedi, Erhard Rahm
2019	Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being.	Ehimwenma Nosakhare, Rosalind W. Picard
2019	Spatio-temporal Event Forecasting and Precursor Identification.	Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala
2019	Semantic Product Search.	Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Allen Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin

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Comparable venues

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