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ICBDM' 2026: International Conference on Big Data Management

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截稿日期:
2026-05-15 Extended
通知日期:
2026-06-15
会议日期:
2026-06-24
会议地点:
Derby, UK
届数:
8
浏览: 1978   关注: 0   参加: 0

会伴指数 (CP-I)

45.6 / 100
全站第 2,700 名 / 共 5,687 个会议 · 前 48%

数据挖掘与数据库 第 160 / 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%)
59
社区关注 (10%)
10
资料公开度 (15%)
35

用到的输入: 有据可查的届次：8 · 过去 24 个月打开过本页的研究者：3 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 2026-09-25

征稿

ICBDM' 2026 (International Conference on Big Data Management) is an academic conference held in Derby, UK on 2026-06-24. The paper submission deadline is 2026-05-15 (extended). Acceptance notifications are sent on 2026-06-15.

Topics of interest for submission include, but are not limited to: Track 1: Big Data Analysis and Management Data Acquisition, Integration, Cleaning, and Best Practices Big Data Search Architectures, Scalability and Efficiency Cloud/Grid/Stream Data Mining- Big Velocity Data Semantic-based Data Mining and Data Pre-processing Big Data as a Service Data Lifecycle Management: From Collection to Archiving Data Governance Frameworks and Best Practices Data Management Standards (e.g., FAIR principles: Findable, Accessible, Interoperable, Reusable) Ethical Considerations in Data Management Algorithms and Systems for Big Data Search Visualization Analytics for Big Data Challenges in Managing Large-scale Datasets Big Data Processing Frameworks (e.g., Apache Spark, Apache Flink) Scalable Storage Solutions for Big Data Mobility and Big Data Methods for Data Collection: Surveys, Experiments, Sensors, Web Scraping Data Integration Techniques: ETL (Extract, Transform, Load) Processes Search and Mining of Variety of Data including Scientific and Engineering, Social, Sensor/IoT/IoE, and Multimedia Data Track 2: Data Structures and Data Models Multimedia and Multi-structured Data- Big Variety Data Computational Modeling and Data Integration Relational Databases (e.g., SQL) vs. NoSQL Databases (e.g., MongoDB, Cassandra) Data Warehousing and Data Lake Architectures Cloud-based Data Storage Solutions (e.g., AWS S3, Google BigQuery) Distributed Storage Systems for Big Data (e.g., Hadoop HDFS) Data Quality Metrics: Accuracy, Completeness, Consistency, and Timeliness Techniques for Data Cleaning and Preprocessing Handling Missing Data: Imputation Methods and Strategies Outlier Detection and Treatment in Datasets Real-Time Data Collection and Streaming Data Management Importance of Metadata in Data Management Metadata Standards and Schemas (E.G., Dublin Core, Schema.Org) Tools for Metadata Extraction and Management Role of Metadata in Data Discovery and Reuse Visualization of High-Dimensional Data Managing Unstructured Data (E.G., Text, Images, Videos) Data Silos and Interoperability Issues Track 3: Big Data Security and Privacy Visualizing Large Scale Security Data Threat Detection using Big Data Analytics Privacy Threats of Big Data Privacy Preserving Big Data Collection/Analytics HCI Challenges for Big Data Security & Privacy Sociological Aspects of Big Data Privacy Trust Management in IoT and Other Big Data Systems Data Encryption and Anonymization Techniques Role-based Access Control (RBAC) and Data Permissions Compliance with Data Protection Regulations (e.g., GDPR, CCPA) Secure Data Sharing and Transfer Protocols Visualizing Large Scale Security Data Balancing Data Accessibility with Security Trust Management in IoT and Other Big Data Systems HCI Challenges for Big Data Security & Privacy Track 4: Big Data Analysis Tools and Key Technologies Healthcare: Managing Electronic Health Records (EHR) and Patient Data Finance: Data Management for Fraud Detection and Risk Analysis Environmental Science: Managing Climate and Satellite Data Social Sciences: Handling Survey and Census Data E-Commerce: Customer Data Management and Personalization Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication Big Data Analytics in Small Business Enterprises (SMEs) Big Data Analytics in Government, Public Sector and Society in General Real-Life Case Studies of Value Creation through Big Data Analytics Experiences with Big Data Project Deployments Big Data as a Service Big Data Industry Standards Track 5: Application of Big Data in Information Systems Tools and Techniques for Exploratory Data Analysis (EDA) Interactive Dashboards for Data Exploration (E.G., Tableau, Power BI) Open-Source Data Management Tools (E.G., Apache Nifi, Talend) Data Management Platforms (E.G., Snowflake, Databricks) Cloud-Native Data Management Solutions Automation Tools for Data Pipelines (E.G., Airflow, Prefect) Data Pipelines for Machine Learning Workflows Feature Engineering and Dataset Preparation Managing Labeled and Unlabeled Data for Supervised and Unsupervised Learning Data Versioning and Reproducibility in ML Experiments Data Management for AI and Deep Learning Blockchain for Secure and Decentralized Data Management Federated Learning and Privacy-Preserving Data Management Quantum Computing and Its Impact on Data Management
由 Dunn Carl 最后更新于

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