【Call for papers】SIGKDD-2023(CCF-A/数据挖掘/2023年2月2日截稿)
29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING.
文章目录
- 1.会议信息
- 2.时间节点
- 3.论文主题
1.会议信息
会议介绍: 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING.
会议全称: ACM Knowledge Discovery and Data Mining
会议网址: https://kdd.org/kdd2023/
会议地点: Long Beach, CA
CCF分类: A 类
Core分类: A* 类
H5指数: 90
影响力值: 13.53
录取率: KDD-22,录取率:KDD’22 14.98% (254/1695)
2.时间节点
When | What |
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Feb 2, 2023 | Paper submission |
May 18, 2023 | Final notification |
June 10, 2023 | Camera-ready |
August 6-10, 2023 | Conference |
3.论文主题
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Data Science: Methods for analyzing scientific and business data, social networks, time series; mining sequences, streams, text, web, graphs, rules, patterns, logs data, IoT data, spatio-temporal data, biological data; recommender systems, computational advertising, multimedia, finance, bioinformatics.
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Big Data: Large-scale systems for text and graph analysis, machine learning, optimization, sampling, parallel and distributed data science (cloud, map-reduce, federated learning), novel algorithmic and statistical techniques for big data, data cleaning and preparation that uses learning, algorithmically efficient data transformation and integration.
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Foundations: Models and algorithms, asymptotic analysis; model selection, dimensionality reduction, relational/structured learning, matrix and tensor methods, probabilistic and statistical methods; deep learning, transfer learning, representation learning, meta learning, reinforcement learning; classification, clustering, regression, semi-supervised, self-supervised learning, few shot learning and unsupervised learning; personalization, security and privacy, visualization; fairness, interpretability, ethics and robustness.