会议信息

BDCAT 2026: IEEE/ACM International Conference on Big Data Computing, Applications and Technologies

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BDCAT
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截稿日期:
2026-09-11 Extended
通知日期:
2026-10-10
会议日期:
2026-12-01
会议地点:
Florianopolis, Brazil
届数:
ICORE: C   浏览: 25467   关注: 13   参加: 4

会伴指数 (CP-I)

57.4 / 100
全站第 699 名 / 共 5,682 个会议 · 前 13%

数据挖掘与数据库 第 36 / 337

学术认可 (35%)
58
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
71
社区关注 (10%)
47
资料公开度 (15%)
55

用到的输入: 收录等级：ICORE C · 有据可查的届次：13 · 在会伴关注它的研究者：13 人 · 过去 24 个月打开过本页的研究者：16 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-18

征稿

BDCAT 2026 (IEEE/ACM International Conference on Big Data Computing, Applications and Technologies) is a ICORE C conference held in Florianopolis, Brazil on 2026-12-01. The paper submission deadline is 2026-09-11 (extended). Acceptance notifications are sent on 2026-10-10.

Conference Overview Recent years have witnessed significant interest in the use of Machine Learning and AI-based techniques to support large-scale data analysis, with research and implementation of systems specifically focused on supporting different phases of the data processing lifecycle. These have ranged from in-memory systems and distributed environments (e.g., MapReduce/Hadoop, Spark) to specialist environments for stream processing of data and events (e.g., Flink, Kinesis) and Serverless (e.g., OpenWhisk, AWS Lambda). We also recognize the importance of computational systems required to process small data volumes, but which involve interdependencies and relationships that are hard to capture and derive. The International Conference on Big Data Computing, Applications and Technologies (BDCAT) is a premier annual international conference series aiming to provide a forum for researchers from both academia and industry to present and discuss new discoveries in the broad area of big data computing and applications. The IEEE/ACM BDCAT 2026 will be held in conjunction with the 19th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2026) in Florianopolis, Brazil. Call for Papers Details Authors are invited to submit original, unpublished research manuscripts in all areas of Big Data computing, applications, and technologies, as well as on related scaling data analysis. Topics of interest include (but are not limited to): Machine Learning and Data Mining Data Science Models and Approaches Supervised, Unsupervised, Semi-supervised, and Reinforcement Learning Neural Networks, Convolution Neural Networks, and Recurrent Neural Networks Autoencoders, Transformers, Large Language Models Natural Language Understanding, Natural Language Processing Swarm Intelligence and Evolutionary Strategy Computational Efficient Model Training, Inference, and Serving Distributed, Federated, and Parallel Learning Algorithms Fairness, Interpretability, and Explainability Data Processing and Infrastructures/Platforms Data Acquisition, Integration, Cleaning, and Best Practices Scalable Computing Models, Theories, and Algorithms MapReduce: Hadoop and Spark Privacy and Security over the Data Life Cycle Data Search and Information Retrieval Techniques Extract/Transform/Load (ETL) or ETL Pipelines In-Memory Systems and Platforms Performance Evaluation Reports Storage Systems (including file systems, NoSQL, and RDBMS) Resource Management Approaches Data Analytics on Edge Devices Fault Tolerance and Reliability Energy-Efficiency and Sustainability Data Archival and Preservation Testing, Debugging, and Monitoring Specialized Hardware for Scaling Applications Domains Internet of Things, Mobile Applications, and Cyber-Physical Systems Healthcare and Life Science (e.g., Genome Processing) Physical Science and Engineering Business and Enterprise Applications Social Network Analysis Scientific Case Studies and Workflows Risk Analysis and Management Cloud-Edge Continuum Data Streaming and Batch Applications Data Trends and Challenges Data Visualization and Analytics Visual Analytics Algorithms and Foundations Graph and Context Models for Visualization Analytics Reasoning and Sense-making Visual Representation and Interaction Data Transformation and Presentation
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