会議情報

RDAAPS 2021: Reconciling Data Analytics, Automation, Privacy, and Security

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RDAAPS
投稿締切日:
2020-12-21
通知日:
2021-02-22
開催日:
2021-05-17
開催地:
Hamilton, Ontario, Canada
閲覧: 11556   フォロー: 0   参加: 0

論文募集

RDAAPS 2021 (Reconciling Data Analytics, Automation, Privacy, and Security) is an academic conference held in Hamilton, Ontario, Canada on 2021-05-17. The paper submission deadline is 2020-12-21. Acceptance notifications are sent on 2021-02-22.

The International Conference on RDAAPS is an annual forum on research in the broadly defined area of data analytics. RDAAPS brings together researchers from academia, industry, and public sector to present and discuss various aspects of data analytics, including privacy, security, and automation. This venue is meant to bring together stakeholders whose interests lie at the interface of these concerns, providing a platform for integrating the needs of industry with the state-of-the-art scientific advancements, and inspiring original research on solving enterprise data challenges. RDAAPS seeks papers presenting original research in the areas included, but are not limited to: Big Data Analytics for Decision Making New models and algorithms for data analytics Scalable data analytics Optimization methods in data analytics Theoretical analysis of data systems Analytical reasoning systems Decision making under uncertainty Learning systems for data analytics Large-scale text, speech, image, or graph processing systems Accountable Data Analytics Privacy-aware data analytics Fairness in data analytics Interpretable and transparent data analytics Incorporating legal and ethical factors into data analytics Strings in Data Analytics Patterns in Big Data Data compression Bioinformatics Algorithms and data structures for string processing Useful data structures for Big Data Data structures on secondary storage Security in Data Analysis Traceability of decision making Models for forecasting cyber-attacks and measuring impact Data usage in mounting security threats Data analytics for better situational awareness Domain knowledge modeling and generation Novel ontology representations Scalability of domain-based reasoning on big data Modeling and analyzing unstructured data sets Automation for data analytics, security, and privacy in manufacturing Application of data analysis in manufacturing Big data in Industry 4.0 Privacy and security in manufacturing Challenges of automation of data analytic processes Case studies of the automation of data analytics processes Architecture for data analytics and security Built-in privacy and security in data analytics automation
最終更新：Dou Sun（）

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