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【Call for papers】SIGKDD-2023(CCF-A/数据挖掘/2023年2月2日截稿)

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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

WhenWhat
Feb 2, 2023Paper submission
May 18, 2023Final notification
June 10, 2023Camera-ready
August 6-10, 2023Conference

3.论文主题

  • 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.

  • 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.

  • 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.

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