Conference Information

Deep-BDB 2022: International Conference on Deep Learning, Big Data and Blockchain

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Deep-BDB
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Submission Date:
2022-03-10
Notification Date:
2022-05-20
Conference Date:
2022-08-22
Location:
Rome, Italy
Years:
3
Viewed: 15750   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

39.5 / 100
Ranked #5,106 of 5,647 conferences · Top 91%

#310 of 336 in Data Mining & Databases #328 of 357 in Security & Privacy #653 of 734 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
37
Community attention (10%)
8
Public record completeness (15%)
25

Inputs used: Editions on record: 3 · Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-03

Call For Papers

Deep-BDB 2022 (International Conference on Deep Learning, Big Data and Blockchain) is an academic conference held in Rome, Italy on 2022-08-22. The paper submission deadline is 2022-03-10. Acceptance notifications are sent on 2022-05-20.

Deep and machine learning are the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionize industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, security, manufacturing, education, games, and various other industrial applications. All such fields produce and consume massive amount of big data, which include, for example, online commerce data (marketing data, customer reviews, customer relationship), transportation data (road sensors, cameras, GPS), and data about healthcare, social media, and various other applications. Deep learning techniques and big data techniques yield useful outputs in predicting, discovering and acquiring insights and deeper knowledge about events for better and efficient decision making. The groundbreaking technology of blockchain technology also enable decentralization, immutability, and transparency of data and applications. It has been exploited in modern research and industrial domains in order to achieve high level of trust, security and reliable execution of applications and data which are shared across a network of computers. The International Conference on Deep Learning, Big Data and Blockcain aims to enable synergy between these areas and to provide a leading forum for researchers, developers, practitioners, and professional from public sectors and industries in order to meet and share latest solutions and ideas in solving cutting edge problems in modern information society and economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Topics of interest include (but not limited to): Deep/Machine learning based models Statistical models and learning Data analysis, insights and hidden pattern Data analysis and decision making Data wrangling, munching and cleaning Data integration and fusion Data visualization Data and information quality Security threat detection Visualizing security threats Enhancing privacy and trust Data mining; Information extraction; Sentiment analysis Data classification and clustering Knowledge acquisition and learning Clustering, classification and regression Supervised and unsupervised learning Blockain security and trust Blockchain data management Data & application reliability Blockchain and data distribution Blockain and finacial transactions Blockchain and Bitcoin applications Blockain and NoSQL databases Protocols for blockchain Cryptography, Cryptocurrency Fraud detection and prevention Blockchain and Internet of Things Scalability of blockchains Application areas: Finance, business and retail Intelligent transportation Healthcare and clinical decision support Bioinformatics and biomedical informatics Computer vision Human activity recognition Cybersecurity Natural language processing Recommender systems Social media and networks
Last updated by Dou Sun on

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