会議情報

SmartData 2026: IEEE International Conference on Smart Data

投稿締切日:
2026-06-15 締切済み
通知日:
2026-09-01
開催日:
2026-11-30
開催地:
Montbeliard, France
開催回数:
12
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会伴インデックス (CP-I)

50.2 / 100
全 5,776 件中 第 1,679 位 · 上位 30%
学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%)
69
コミュニティの注目度 (10%)
37
公開情報の充実度 (15%)
35

使用した入力: 確認できる開催回数：12 · 会伴でフォローしている研究者：7 人 · 過去 24 か月にこのページを開いた研究者：8 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 過去の開催回 (+3.0) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 45% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.2 · 算出日 2026-11-13

論文募集

SmartData 2026 (IEEE International Conference on Smart Data) is an academic conference held in Montbeliard, France on 2026-11-30. The paper submission deadline is 2026-06-15. Acceptance notifications are sent on 2026-09-01.

Introduction Smart data aims to filter out the noise data and produce valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making. Although unprecedentedly large amount of sensory data can be collected with the advancement of the Cyber-Physical-Social systems, the key is to explore how big data can become smart data and offer intelligence. Advanced big data modeling and analytics are indispensable for discovering the underlying structure from retrieved data and further acquiring smart data. The IEEE SmartData 2026 is to promote community-wide discussion identifying the computational intelligence technologies and theories for harvesting smart data from big data. It will provide a high-profile, leading-edge forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences and work-in-process on all aspects of smart data. Topics for submissions include but are not limited to the following theory, technology, and applications. Topics Topics for submissions include but not limited to the following: Track 1: Data Governance, Ethics & Foundations AI and Data Ethics Data Privacy & Security in the Age of LLMs Data Provenance, Trust & Lineage Fairness, Accountability & Transparency (FAT) in AI Modern Data Governance Strategies & Frameworks Data Quality, Cleaning & Integration Distributed & Decentralized Data Systems Blockchain for Data Management Track 2: Smart Data Infrastructure & Systems Cloud, Edge & Fog Computing for Smart Data High-Performance & Parallel Computing for Big Data Open Source Big Data Ecosystems (Spark, Flink, etc.) System Architectures for Smart Data Pipelines Energy-Efficient & Green Data Processing 6G-Enabled Data Infrastructure Serverless & Microservices Architectures Data Streaming & Real-Time Processing Track 3: Machine Learning & AI Algorithms Core Machine Learning & Deep Learning Algorithms Generative AI & Large Language Models (LLMs) Reinforcement Learning & Decision Making Federated & Collaborative Learning Transfer Learning & Domain Adaptation Explainable AI (XAI) & Interpretable Models Graph Neural Networks & Geometric Deep Learning Nature-Inspired & Evolutionary Computing Foundation Models & Multimodal AI Track 4: AI-driven Analytics & Cybersecurity Secure & Privacy-Preserving Analytics AI for Cybersecurity & Threat Intelligence Social Media, Web & Behavioral Analytics Graph Analytics & Network Science Anomaly Detection & Intrusion Detection Systems LLM-based Security Analysis & Vulnerability Detection Track 5: Smart Data Applications Smart Data Applications in All Fields (Health, Finance, etc.) Data as a Service (DaaS) & Data Marketplaces Smart City & Urban Computing Autonomous Systems & Self-Driving Vehicles Crowdsourcing & Human-in-the-Loop Systems Digital Twins & Simulation-Driven Data Ethical & Societal Impact of Smart Data Applications Track 6: Smart Data in Internet of Things (IoT) Network Design, Scheduling & Optimization for IoT Age of Information for Data Collection & Analytics in IoT Learning-Based Decision-Making with Smart Data in IoT Mobile Data Collection, Transmission & Analytics in IoT TinyML & Edge AI for Resource-Constrained IoT Devices Security & Privacy in IoT Data Ecosystems IoT Data Protocols & Standards (MQTT, CoAP, Matter) Ambient Intelligence & Smart Environment Sensing
最終更新：Dou Sun（）

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関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
IEEE Transactions on Smart Grid9.8IEEE1949-3053
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.5Elsevier0167-8655
BPattern Recognition9.1Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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