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IEEE BigData 2026: IEEE International Conference on Big Data

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IEEE BigData
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Día de Entrega:
2026-08-21
Fecha de Notificación:
2026-10-24
Fecha de conferencia:
2026-12-14
Ubicación:
Phoenix, Arizona, USA
CCF: C   ICORE: B   Vistas: 55488   Seguidores: 20   Asistentes: 6

Índice Conference Partner (CP-I)

56,6 / 100
Puesto n.º 748 de 5.683 congresos · 14% superior

N.º 39 de 337 en Minería de datos y bases de datos

Reconocimiento académico (35%)
72
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Atención de la comunidad (10%)
62
Integridad del registro público (15%)
35

Datos utilizados: Categorías: CCF C, ICORE B · Investigadores que lo siguen aquí: 20 · Investigadores que abrieron esta página en los últimos 24 meses: 72

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Ediciones anteriores (+3,0) · Premios al mejor artículo (+2,3)
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Confianza 60 %: la parte de la puntuación respaldada por datos observados y no por la línea base neutra. Cómo se calcula esta puntuación · Ver la clasificación · Versión del algoritmo 1.1 · Calculado el 2026-09-21

Solicitud de Artículos

IEEE BigData 2026 (IEEE International Conference on Big Data) is a CCF C / ICORE B conference held in Phoenix, Arizona, USA on 2026-12-14. The paper submission deadline is 2026-08-21. Acceptance notifications are sent on 2026-10-24.

Topics of Interest: Big Data Science and Foundations New Data Standards Data and Information Quality for Big Data New Computational Models for Big Data Novel Theoretical Models for Big Data Big Data Infrastructure Software Systems to Support Big Data Computing New Programming Models for Big Data beyond Hadoop /MapReduce, STORM Big Data Open Platforms Software Techniques and Architectures in Cloud /Grid /Stream Computing Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data Energy-efficient Computing for Big Data Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment High Performance /Parallel Computing Platforms for Big Data Cloud /Grid /Stream Computing for Big Data Big Data Management Compliance and Governance for Big Data Multimedia and Multi-structured Data- Big Variety Data Mobility and Big Data Cloud/Grid/Stream Data Mining- Big Velocity Data Large-scale Recommendation Systems and Social Media Systems Computational Modeling and Data Integration Data Acquisition, Integration, Cleaning, and Best Practices Big Data Search and Mining Search and Mining of a variety of data, multimedia data. social, sensor /IoT /IoE, and including scientific and engineering, Data Ecosystem Experimental studies of fairness, diversity, accountability, and transparency Ecosystem assessment, valuation, and sustainability Trust management in Big Data systems Privacy preserving Big Data collection/analytics Trust, resilience, privacy, and security issues Methods for data exchange, monetization, and pricing Ecosystem services and management Data concepts, theory, structure, and process Foundation Models for Big Data Foundation Model Operationalization for multiple users Prompt Engineering and its Management Big data management for prompt-tuning Big data management for fine-tuning Big data management for pre-training Big Data Applications Complex Big Data Domain Applications in Engineering Human Resources Cybersecurity Industrial IoT Media and Entertainment Telecommunication Advertising Marketing Supply Chains Retailing Transportation Logistics Education Law Business Finance Urban Planning Smart Cities Big Data for Science Science Knowledge Foundation Models AI-accelerated Simulations and Modeling AI-Ready Scientific Big Data Systems and Analysis Medicine and Health Science Chemical Engineering and Synthetic Biology Materials Informatics Geospatial and Planetary Analytics Climate and Earth Sciences Genomics and Bioinformatics, Structural Biology Science Computational Astrophysics AI-Driven Scientific Discovery in Physical Sciences Big Data Benchmarks Responsible Dataset Development Advanced Collection and Curation Practices Data-Centric AI Methods, Tools, and Systems Data Generators and Synthetic Environments Benchmarking Tools and Platforms Benchmarks and Evaluation Frameworks New Datasets and Collections Big Data BlueSky Ideas Novel Interdisciplinary Synthesis Paradigm-Shifting Applications Foundational Assumption Challenges New Algorithmic Opportunities Complex and Hard Problem Solving Trending, Emerging, Bold, or Visionary Concepts
Última actualización por Dou Sun el

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