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ICBDR 2026: International Conference on Big Data Research

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截稿日期:
2026-05-10 Extended
通知日期:
2026-05-25
会议日期:
2026-06-12
会议地点:
Chengdu, China
届数:
7
浏览: 15417   关注: 0   参加: 0

会伴指数 (CP-I)

45.5 / 100
全站第 2,708 名 / 共 5,682 个会议 · 前 48%

数据挖掘与数据库 第 161 / 337

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
56
社区关注 (10%)
16
资料公开度 (15%)
35

用到的输入: 有据可查的届次：7 · 过去 24 个月打开过本页的研究者：7 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 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 45% —— 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 2026-09-16

征稿

ICBDR 2026 (International Conference on Big Data Research) is an academic conference held in Chengdu, China on 2026-06-12. The paper submission deadline is 2026-05-10 (extended). Acceptance notifications are sent on 2026-05-25.

We encourage original submissions related to, but not limited to, the following advanced energy materials based system topics: Big Data Models and Algorithms Foundational Models for Big Data Algorithms and Programming Techniques for Big Data Processing Big Data Analytics and Metrics Representation Formats for Multimedia Big Data Advances in Neural Networks and Deep Learning for Large-Scale Data Analytics Evolutionary Computation and Genetic Algorithms for Big Data Optimization Fuzzy Systems for Uncertain and Complex Data Modeling Decentralized and Self-Organizing Networks for Scalable Data Clustering Self-Adaptive Architectures for Real-Time Big Data Stream Processing Bio-Inspired Self-Organization in Edge Computing and IoT Data Fusion Big Data Architectures Cloud Computing Techniques for Big Data Big Data as a Service Big Data Open Platforms Big Data in Mobile and Pervasive Computing Real-Time Big Data Processing and Stream Architectures Scalable Storage Systems for Big Data Edge and Fog Computing for Big Data AI-Driven Big Data Architecture Design Energy-Efficient Big Data Systems Privacy-Preserving Big Data Architectures Big Data Management Big Data Persistence and Preservation Big Data Quality and Provenance Control Big Data Storage and Retrieval Adaptive Distributed Storage: Self-Optimizing Architectures for Scalable Data Lakes Self-Healing Data Backup Strategies in Decentralized Environments Autonomic Indexing and Retrieval in Large-Scale Unstructured Data Networks Energy-Efficient Self-Organization for Edge-Based Big Data Processing Bayesian Nonparametrics for Anomaly Detection in High-Velocity Data Streams Robust Statistical Cleaning of Noisy Heterogeneous Datasets Causal Inference Frameworks for Data Quality Root-Cause Analysis Big Data Security and Privacy Big Data System Security and Integrity Big Data Information Security Privacy Preserving Big Data Analytics Secure Multi-Party Computation for Big Data Blockchain-Based Big Data Security Solutions Differential Privacy in Big Data Systems AI-Powered Threat Detection in Big Data Compliance and Regulatory Challenges in Big Data (GDPR, CCPA, etc.) Secure Data Provenance and Auditing Adversarial Attacks and Defenses in Big Data Analytics Big Data in Smart Cities Big Data for Improving Resilient Infrastructures Big Data Applications such as Healthcare and Transportation Big Data for Enterprise, Government, and Society Big Data for Science and Engineering Research Deep Learning for Smart City Traffic Flow Prediction and Optimization Fuzzy Logic-Based Demand Response in Smart Grids: Handling Uncertainty in Energy Load Forecasting Large-Scale Satellite Image Processing: Machine Learning for Deforestation and Carbon Emission Monitoring Bayesian Uncertainty Quantification in Climate Risk Assessment Big Data Search, Mining, and Visualization Algorithms and Systems for Big Data Search Distributed, and Peer-to-peer Search Machine learning based on Big Data Visualization Analytics for Big Data Interactive and Real-Time Big Data Visualization Explainable AI (XAI) for Big Data Mining Graph Mining and Network Analysis at Scale Natural Language Processing (NLP) for Big Text Data Multimodal Big Data Fusion and Mining Human-in-the-Loop Big Data Analytics
由 Dunn Carl 最后更新于

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