Journal of Big Data is now indexed in the Science Citation Index Expanded (SCIE)! The first Impact Factor and Ranking will be published in the June release of the Journal Citation Report.
Journal News
Call for papers: Applications and development in Linked Open Data (LOD) cloud
This special issue proposal intends to capture the state-of-the-art applications and technologies such as the semantic web, machine learning, deep learning, natural language processing, internet of things, knowledge graph, process mining, and artificial intelligence, etc. which encompasses the wider spectrum of the Linked Open Data (LOD).
Call for papers: Advanced bio-inspired deep learning algorithms for multi-modal perceptual big data analysis in car-driver assistance systems
Next generation cars collect a wide variety of data coming from different systems that need to be processed and merged in order to provide adequate car driving assistance. The thematic series will look at approaches to car-driver assistance systems that make use of sophisticated bio-inspired algorithms and modern deep learning approaches.
Articles
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Neural network training with limited precision and asymmetric exponent
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Classification of mastoid air cells by CT scan images using deep learning method
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A unified representation and transformation of multi-model data using category theory
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A systematic review and research perspective on recommender systems
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A survey on Image Data Augmentation for Deep Learning
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Big data in healthcare: management, analysis and future prospects
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Deep learning applications and challenges in big data analytics
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Sentiment analysis using product review data
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Short-term stock market price trend prediction using a comprehensive deep learning system
Aims and scope
The Journal of Big Data publishes open-access original research on data science and data analytics. Deep learning algorithms and all applications of big data are welcomed. Survey papers and case studies are also considered.
The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.
The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.
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Annual Journal Metrics
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Speed
48 days to first decision for all manuscripts
40.7 days to first decision for reviewed manuscripts only
108 days from submission to acceptance
18 days from acceptance to publicationCitation Impact
2.501 - Source Normalized Impact per Paper (SNIP)
0.925 - SCImago Journal Rank (SJR)
6.1 - CiteScore
Usage
1,878,037 downloads (2021)
549 Altmetric mentions
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- ISSN: 2196-1115 (electronic)