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BigDataService 2020 : 6th IEEE Intl. Conf. on Big Data Computing Services and Machine Learning Applications

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Link: http://big-dataservice.net/
 
When Apr 13, 2020 - Apr 16, 2020
Where Oxford, UK
Submission Deadline Dec 1, 2019
Notification Due Jan 15, 2020
Final Version Due Jan 30, 2020
Categories    big data   machine learning   service-oriented technologies
 

Call For Papers

6th IEEE Intl. Conf. on Big Data Computing Services and Machine Learning Applications (BigDataService 2020)
13-16 April 2020, Keble College, Oxford UK

CALL FOR PAPERS
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BigDataService seeks to include work from a wide range of technologies and domains – including (but not limited to) smart systems (e.g. cities, automobiles, farms), cyber-physical systems, Internet of Things applications, healthcare, and social networks and media. Technological aspects of the event include service-oriented technologies, machine learning, predictive analytics, data modelling, system architectures, data mining, and simulation.

The main conference will be co-located with IEEE SOSE 2020, IEEE MobileCloud 2020 and IEEE DAPPS 2020, and IEEE AITest 2020, and will consist of main tracks and special tracks.





The conference seeks the submission of high-quality full papers limited to up to 8 pages (IEEE format) in length. The submission of short, demo or industry papers limited to up to 4 pages (IEEE format) is possible, for works that make significant contributions, but are still in progress, or works of smaller scale that can be reported briefly.

The deadline for paper submission is on October 20th 2019. All accepted papers will be included in the IEEE proceedings. Selected papers will be invited for extension and published in journals (SCI- Index). The conference also welcomes workshop proposals – with a deadline of December 1st 2019.

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TOPICS OF INTEREST (INCLUDE BUT NOT LIMITED TO)
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Big Data Analytics and Mining
- Algorithms and systems for big data search and analytics
- Predictive analytics and simulation
- Big data visualization and interactive data exploration
- Big data mining applications
- Knowledge extraction, discovery, analysis, and presentation

Big Data Foundations
- Foundational theoretical or computational models for big data
- Programming models, theories, and algorithms for big data
- Standards, protocols, and quality assurance for big data

Big Data Platforms and Technologies
- Innovative, concurrent, and scalable big data platforms
- Data indexing, cleaning, transformation, and curation technologies
- Big data processing frameworks and technologies
- Big data services and application development methods and tools
- Big data quality evaluation and assurance technologies
- Big data system reliability, dependability, and availability
- Open-source development and technology for big data
- Big Data as a Service (BDaaS) platform and technologies
- Big data search (architecture, algorithms, scalability)

Integrated and Distributed Systems
- Foundational theoretical or computational models for big data
- Programming models, theories, and algorithms for big data
- Standards, protocols, and quality assurance for big data
- Sensor networks, IoT, Smart systems

Big Data and Machine Learning Applications and Experiences
- Innovative big data applications and services in industries and domains e.g. healthcare, finance, insurance, transportation, agriculture, education, environment, multi-media, social networks, urban planning, disaster management, security
- Big data analytics in the public sector
- Large-scale recommendation systems
- Link and graph mining, social network mining
- Mobility and big data
- Stream data mining
- Experiences and case studies of big data applications and services
- Real-world and large-scale practices of big data

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SPECIAL TRACKS
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Special Track on Real-time Big Data Services and Applications
- Models, algorithms, and technologies for real-time big data services and applications
- Experiences, practices and case studies of real-time big data services and applications

Special Track on Big Data Security, Ethics, Privacy and Trust
- Models, algorithms and technologies for big data security and integrity
- Practical security and privacy technologies and applications for big data
- Models, algorithms, and techniques for fairness and diversity in big data applications
- Transparency and interpretability vs. Privacy

Special Track on Big Data and analytics for Healthcare
- Models, algorithms, and technologies of big data for healthcare
- Big data services and applications for healthcare
- Experiences, practices and case studies of big data technologies for healthcare

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PAPER SUBMISSION
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Papers must be written in English. All papers must be prepared in the IEEE double column proceedings format. Please see the following link for details: http://www.ieee.org/conferences_events/conferences/publishing/templates.html. Research and survey papers are limited to 8 pages, and short, demo or industry papers are limited to 4 pages.

Authors must submit their papers at:

https://easychair.org/my/conference?conf=bds20200

IEEE BigDataService 2020 also welcomes workshop and tutorial proposals – with a deadline of October 30th 2019.

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PAPER PUBLICATION
-----------------

All accepted papers will be published by IEEE Computer Society Press (EI‐Index) and included in IEEE
Digital Library. For publication, at least one author is required to register at the full rate and present
the paper at the conference for the paper to be included in the final technical program and the IEEE
Digital Library. Selected papers will be invited for extension and published in journals (SCI-Index).

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GENERAL CHAIRS
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Fanjing Meng, IBM Research, China
Jerry Gao, San Jose State University, USA

PC CHAIRS
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Iraklis Varlamis, Assoc. Professor, Harokopiο University of Athens, Greece
Magdalini Eirinaki, San Jose State University, CA, USA
Paul Townend, Edgetic Ltd., UK

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