Special Session 1:

4th Special Session on HealthCare Data

December 15-18, 2021 @ Orlando, FL, USA

Health data differs from other industries' data in terms of structure, context, importance, volatility, availability, traceability, liquidity, change speed, usage and sources from which it is collected. As medicine is a constantly developing science, healthcare sector also. In this new emerging research area which stands at the intersection of several different discipline such as Medicine, Behavioral Science, Supply Chain Management or Big Data Analytics, techniques, methods, applications and devices are continuously developed to be used for the acquisition, storage, processing, analysis, standardization and optimization of every process in the health sector. As the healthcare sector is so challenging and related data are consistently explosive, healthcare organizations are focusing to become smarter in order to overcome the industry’s inefficiencies to improve quality of care. “To become smarter” requires impeccable data analytics. All stakeholders in the sector should reveal the deep value of this valuable data in order to apply insights to improve quality of care, clinical outcomes and deliver personalized healthcare value, while reducing medical costs, collaborate across care settings to deliver integrated, personalized care experiences, prevent disease, promote wellness and manage care, build flexibility into operations to support cost reduction and excellence in clinical and business performance and practices.

The general purpose of this special session in IEEE BigData 2021 conference is to bring together researchers, academicians and sector employees from different fields and disciplines and provide them an independent platform to exchange information on their researches, ideas and findings about healthcare data and its analytics. It is also aimed to encourage debate on how big data can effectively support healthcare in terms of diagnosis, treatment and population health, and to develop a common understanding for research conducted in this multidisciplinary field.

Topics of interest include, but are not limited to, the following:

  • Healthcare Data
  • Health data collection and analysis
  • Problems in health data processing
  • Protection and security of personal health data
  • Electronic health records and standards
  • Healthcare Information Systems
  • Medical Imaging Systems
  • Medical Applications
  • Mobile Solutions
  • Pervasive Healthcare Information Systems and Services
  • Sensor nodes
  • Wearable health information
  • Information solutions developed for the disabled
  • Process Management in Health Informatics Systems
  • Health Decision Support Systems
  • E-health Applications
  • Public health information application
Special Session Organizers
  • Sultan Turhan PhD. (sturhan@gsu.edu.tr), Department of Computer Engineering, Galatasaray University
  • Assist. Prof. Ozgun Pinarer (opinarer@gsu.edu.tr), Department of Computer Engineering, Galatasaray University
Important Dates
  • Abstract submission: September 11, 2021
  • Full paper submission: September 18, 2021
  • Notification of paper acceptance: Nov 6, 2021
  • Camera-ready of accepted papers: Nov 19, 2021
  • Conference: Dec 15-18, 2021
Instructions

Please submit a full-length paper (up to 10 page IEEE 2-column format) through the online submission system. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. Detailed instructions for the authors can be found at the conference website.Accepted papers will be published in the conference proceedings. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings.

Paper submission page: https://wi-lab.com/cyberchair/2021/bigdata21/index.php

Special Session 2:

7th Special Session on Intelligent Data Mining

December 15-18, 2021 Orlando, FL, USA

After the successes of the first, second, third, fourth and fifth editions of Special Session on Intelligent Data Mining in Santa Clara, CA (2015); Washington, DC (2016); Boston, MA (2017); Seattle, WA, (2018); Los Angeles, CA, (2019); Online Pandemic Session (2020) and the seventh Special Session on Intelligent Data Mining in Orlando, FL (2021) will continue promoting and disseminating the knowledge concerning several topics and technologies related to data mining science.

Artificial Intelligence (AI) & Machine Learning (ML) fields are interdisciplinary, including computer science, mathematics, psychology, linguistics, philosophy, neuroscience etc. This interdisciplinary special session seeks scientific understanding on data and intelligence.

This session may help to create scientific evolution to propose robust and powerful schemes between human nature and big data processing.

Intelligent Data Mining session open to every researcher as well as industrial partners.

The aims of this Special Session on Intelligent Data Mining are to:

  • Bring researchers and experts together to discuss and share their experiences
  • Share the current and new research topics and ideas
  • Improve and enhance personal, enterprise, national and international awareness
  • Provide a platform to present and discuss recent advancements
  • Increase international collaborations among university–industry-institutions

In the fields of theory and applications of data mining, artificial intelligence, computer science, mathematics, psychology, linguistics, philosophy, neuroscience and other disciplines to discuss better understanding of big data and intelligence.

The papers submitted to this special session might be in a large range of topics that include theory, application and implementation of artificial intelligence, machine learning and data mining including but not limited to the topics given below.

Use of Artificial Intelligence || Machine Learning in Data Mining as:
  • Data Mining, Data Science and Big Data
  • Data Warehouse, Clustering, Visualization
  • Big Data and Services
  • Graph Mining
  • Data Security and Privacy
  • Homeland Security and Data Analysis
  • Coin Mining and GPU Applications
  • Deep Learning
  • Scalable Computing, Cloud Computing
  • Knowledge Discovery, Integration, Transformation
  • Information Retrieval
  • Data Classification, Regression, Cleaning
  • Smart Cities & Energy
  • Social Media, Social Networking, Social Data
  • Semantic Computing
  • IoT, Autonomous Systems and Agents
  • Algorithms
  • Mobile Computing
  • Sensors, Networks, Devices
  • Mathematics
  • NLP
  • Philosophy
  • Neuroscience and Bioinformatics
  • Biometric
  • Sustainability
  • HPCC and Hadoop
  • Recent Theory, Trends, Technologies and Applications
  • Future Directions and Challenges in Intelligent Data Mining
  • Industrial Challenges in Intelligent Data Mining
  • Demo Applications

Extended versions of all session papers will be published on the International Journal of Data Mining Science

Papers should be submitted for this special session by Sept 10, 2021, at the conference special session submission system.

Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website. Accepted papers will be published in the conference proceedings. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings (http://bigdataieee.org/BigData2021/).

If you have any question about this special session, please do not hesitate to direct your question to the special session organizer Asst. Prof. Dr. Uraz Yavanoglu (urazyavanoglu@gmail.com, uraz@gazi.edu.tr)

Special Session Organizer:
Asst. Prof. Dr. Uraz Yavanoglu
Department of Computer Engineering
Vice-Chairman
Gazi University, Turkey
www.druraz.com

The important dates for this special session are:
Full Paper Submission Deadline : Sept 10, 2021 11:59pm PST
Notification of Acceptance : Nov 5, 2021
Camera-ready papers & Pre-registration : Nov 15, 2021, 11:59pm PST
Conference Dates : Dec 15-18, 2021

Special Session 3:

Machine Learning on Big Data (MLBD 2021)

December 15-18, 2021, Orlando, FL, USA

Best Papers of MLBD 2021 will be Invited for Extended Submission to a Top-Quality Journal

Aim and Scope
The Special Session “Machine Learning on Big Data” (MLBD 2021) of the 2021 IEEE International Conference on Big Data (IEEE BigData 2021) follows the great success of five previous editions co-located with the IEEE BigData and IEEE ICMLA conference series and focuses on machine learning models, techniques and algorithms related to Big Data, a vibrant and challenging research context playing a leading role in the Machine Learning and Data Mining research communities. Big data is gaining attention from researchers, being driven among others by technological innovations (such as cloud interfaces) and novel paradigms (such as social networks). Devising and developing machine learning models, techniques and algorithms for big data represent a fundamental problem stirredup by the tremendous range of critical applications incorporating machine learning tools in their core platforms. For example, in application settings where big data arise and machine is useful, we recognize, among other things: (i) machine-learning-based processing (e.g., acquisition, knowledge discovery, and so forth) over large-scale sensor networks introduces important advantages over classical data-management-based approaches; similarly, (ii) medical and e-heath information systems usually include successful machine learning tools for processing and mining very large graphs modelling patient-to-disease, patient-todoctor, and patient-to-therapy networks; (iii) genome data management and mining can gain important benefits from machine learning algorithms. Some hot topics in machine learning on big data include: (i) machine learning on unconventional big data sources (e.g., large-scale graphs in scientific applications, strongly-unstructured social networks, and so forth); (ii) machine learning over massive big data in distributed settings; (iii) scalable machine learning algorithms; (iv) deep learning – models, principles, issues; (v) machinelearning-based predictive approaches; (vi) machine-learning-based big data analytics; (vii) privacy-preserving machine learning on big data; (viii) temporal analysis and spatial analysis on big data; (ix) heterogeneous machine learning on big data; (x) novel applications of machine learning on big data (e.g., healthcare, cybersecurity, smart cities, and so forth).

The MLBD 2021 special session focuses on all the research aspects of machine learning on Big Data. Among these, an unrestricted list includes:

  • Fundamentals
  • Modelling
  • Statistical Approaches
  • Novel Paradigms
  • Innovative Techniques
  • Algorithms
  • Innovative Architectures (GPU, Clouds, Clusters)
  • Non-Conventional Big Data Settings (e.g., Spatio-Temporal Big Data, Streaming Big Data, Graph Big Data, Cloud Big Data, Probabilistic Big Data, Uncertain Big Data)
  • Systems
  • Architectures
  • Advanced Topics (e.g., Dimensionality Reduction, Matrix Approximation Algorithms, Multi-Task Learning, Semi-Supervised Learning, Integration with NoSQL Databases)
  • Case Studies and Applications

  • The Special Session “Machine Learning on Big Data” (MLBD 2021) of the 2021 IEEE International Conference on Big Data (IEEE BigData 2021) will be held in Orlando, FL, USA, during December 15-18, 2021, and it aims to synergistically connect the research community and industry practitioners. It provides an international forum where scientific domain experts and Machine Learning and Data Mining researchers, practitioners and developers can share their findings in theoretical foundations, current methodologies, and practical experiences on Machine Learning on Big Data. MLBD 2021 will provide a stimulating environment to encourage discussion, fellowship, and exchange of ideas in all aspects of research related to Machine Learning on Big Data. This includes both original research contributions and insights from practical system design, implementation and evaluation, along with new research directions and emerging application domains in the target area. An expected outcome from MLBD 2021 is the identification of new problems in the main topics, and moves to achieve consolidated solutions to already-known problems. Other goals are to help in creating a focused community of scientists who create and drive interest in the area of Machine Learning on Big Data, and additionally to continue on the success of the event across future years.

    Special Session Location
    Orlando, FL, USA

    Submission Guidelines and Instructions
    Contributions are invited from prospective authors with interests in the indicated session topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period.

    Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:

  • Full Papers: 10 pages
  • Short Papers: 4 pages
  • Demo Papers: 4 pages
  • Position Papers: 4 pages

  • Submitted papers will be thoroughly reviewed by members of the Special Session Program Committee for quality, correctness, originality and relevance. All accepted papers must be presented by one of the authors, who must register.

    Papers must be submitted via the CyberChair System by selecting the track “Special Session on Machine Learning on Big Data”.

    Paper Publication
    Accepted papers will appear in the official IEEE Big Data 2021 main conference proceedings, published by IEEE.

    Authors of selected papers from the special session will be invited to submit an extended version of their paper to a special issue of a high-quality international journal.

    Important Dates:
    Paper submission: August 31, 2021
    Notification of acceptance: October 24, 2021
    Camera-ready paper due: November 15, 2021
    Special Session: December 15-18, 2021

    Program Committee Chair
    Alfredo Cuzzocrea, University of Calabria, Italy

    Program Committee
    Michelangelo Ceci, University of Bari, Italy
    Alfredo Cuzzocrea, University of Calabria, Italy
    Joao Gama, University of Porto, Portugal
    Marwan Hassani, TU Eindhoven, The Netherlands
    Mark Last, Ben-Gurion University of the Negev, Israel
    Rocco Langone, Deloitte, Belgium
    Carson K. Leung, University of Manitoba, Canada
    Sofian Maabout, LABRI, Bordeaux University, France
    Anirban Mondal, Shiv Nadar University, India
    Enzo Mumolo, University of Trieste, Italy
    Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece

    For more information and any inquire, please contact Alfredo Cuzzocrea.

    Special Session 4:

    Privacy and Security of Big Data (PSBD 2021)

    December 15-18, 2021, Orlando, FL, USA

    Best Papers of PSBD 2021 will be Invited for Extended Submission to a Top-Quality Journal

    Aim and Scope
    The Special Session “Privacy and Security of Big Data” (PSBD 2021) of the 2021 IEEE International Conference on Big Data (IEEE BigData 2021) follows the great success of seven previous editions co-located with the IEEE BigData and ACM CIKM conference series and focuses the attention on privacy and security research issues in the context of Big Data, a vibrant and challenging research context which is playing a leading role in the Database research community. Indeed, while Big Data is gaining the attention from the research community, also driven by some relevant technological innovations (like Clouds) as well as novel paradigms (like social networks), the issues of privacy and security of Big Data represent a fundamental problem in this research context, due to the fact Big Data are typically published online for supporting knowledge management and fruition processes and, in addition to this, such data are usually handled by multiple owners, with possible secure multi-part computation issues. Some of the hot topics in the context privacy and security of Big Data include: (i) privacy and security of Big Data integration and exchange; (ii) privacy and security of Big Data in data-intensive Cloud computing; (iii) system architectures in support of privacy and security of Big Data, e.g., GPUs: (iv) privacy and security issues of Big Data querying and analysis.

    The PSBD 2021 special session focuses on all the research aspects of privacy and security of Big Data. Among these, an unrestricted list is the following one:

  • Privacy of Big Data: Fundamentals
  • Privacy of Big Data: Modelling
  • Privacy of Big Data: Statistical Approaches
  • Privacy of Big Data: Novel Paradigms
  • Privacy of Big Data: Innovative Protocols
  • Privacy of Big Data: Algorithms
  • Privacy of Big Data: Query Optimization
  • Privacy of Big Data: Non-Conventional Environments (e.g., Spatio-Temporal Data, Streaming Data, Cloud Data, Probabilistic Data, Uncertain Data)
  • Privacy of Big Data: Systems
  • Privacy of Big Data: Architectures
  • Privacy of Big Data: Advanced Topics (e.g., NoSQL Databases)
  • Privacy of Big Data: Case Studies and Applications
  • Security of Big Data: Fundamentals
  • Security of Big Data: Modelling
  • Security of Big Data: Statistical Approaches
  • Security of Big Data: Novel Paradigms
  • Security of Big Data: Innovative Protocols
  • Security of Big Data: Algorithms
  • Security of Big Data: Query Optimization
  • Security of Big Data: Non-Conventional Environments (e.g., Spatio-Temporal Data, Streaming Data, Cloud Data, Probabilistic Data, Uncertain Data)
  • Security of Big Data: Systems
  • Security of Big Data: Architectures
  • Security of Big Data: Advanced Topics (e.g., NoSQL Databases)
  • Security of Big Data: Case Studies and Applications

  • The Special Session on “Privacy and Security of Big Data” (PSBD 2021) of the 2021 IEEE International Conference on Big Data (BigData 2021) will be held in Orlando, FL, USA, during December 15-18, 2021, and it focuses on these aspects, by posing the emphasis on a theoretical as well as a practical point of view, and provides a forum for researchers and practitioners interested in privacy and security of big data to meet and exchange preliminary ideas and mature results.

    Special Session Location
    Orlando, FL, USA

    Submission Guidelines and Instructions
    Contributions are invited from prospective authors with interests in the indicated session topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period.
    Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:

  • Full Papers: 10 pages
  • Short Papers: 4 pages
  • Demo Papers: 4 pages
  • Position Papers: 4 pages

  • Submitted papers will be thoroughly reviewed by members of the Workshop Program Committee for quality, correctness, originality and relevance. All accepted papers must be presented by one of the authors, who must register.

    Papers must be submitted via the CyberChair System by selecting the track “Special Session on Machine Learning on Big Data”.

    Paper Publication
    Accepted papers will appear in the official IEEE Big Data 2021 main conference proceedings, published by IEEE.

    Authors of selected papers from the workshop will be invited to submit an extended version of their paper to a special issue of a high-quality international journal.

    Important Dates:
    Paper submission: August 31, 2021
    Notification of acceptance: October 24, 2021
    Camera-ready paper due: November 15, 2021
    Special Session: December 15-18, 2021

    Program Committee Chair
    Alfredo Cuzzocrea, University of Calabria, Italy

    Program Committee
    Maurizio Atzori, University of Cagliari, Italy
    Roberto Baldoni, University of Rome “Sapienza”, Italy
    Elisa Bertino, CERIAS and Purdue University, USA
    Pietro Colombo, University of Insubria, Italy
    Alfredo Cuzzocrea, University of Calabria, Italy
    Rinku Dewri, University of Denver, USA
    Katerina Doka, NTUA, Greece
    Josep Domingo-Ferrer, Universitat Rovira i Virgili, Spain
    Yucheng Dong, Sichuan University, China
    Murat Kantarcioglu, University of Texas at Dallas, USA
    Thorsten Strufe, Technische Universitat Darmstadt, Germany
    Vicenc Torra, IIIA-CSIC, Spain
    Traian Marius Truta, Northern Kentucky University, USA
    Xiaokui Xiao, Nanyang Technological University, Singapore

    For more information and any inquire, please contact Alfredo Cuzzocrea.

    Special Session 5:

    Information Granulation in Data Science and Scalable Computing

    December 15-18, 2021, Orlando, FL, USA

    BACKGROUND:
    Granular Computing is a general computation approach for a usage of information granules such as data blocks, clusters, groups, as well as value intervals, sets, hierarchies, etc. to build efficient computational models for complex Big Data applications, characterized by huge amounts of data and associated domain knowledge. Information Granulation, under different names, has appeared in many related fields, such as information hiding in programming, granularity in artificial intelligence, divide and conquer paradigms in theoretical computer science, interval computing, cluster analysis, fuzzy and rough set systems, neurocomputing, evolutionary computation, quotient spaces, belief functions, approximate computing, deep learning, statistics and many others related with human and machine intelligence. The principles of Granular Computing can be also helpful to design simplified descriptions of complex data systems and to bridge the gap between humans and AI. Herein we may follow the phrase "Information Granules = Fundamental Pieces of Human Knowledge" and treat Information Granulation as a meta-mathematical methodology for Big Data Analytics

    SESSION SCOPE:
    Special Session on Information Granulation in Data Science and Scalable Computing will continue to address the theory and practice of computation of information granules. It will provide researchers from universities, laboratories and industry with the means to present state-of-the-art research results and methodologies for information granules. The session will also make it possible for scientists and developers to highlight their new research directions and new interactions with novel computing models utilizing the concepts of Information Granulation.

    The session will focus – from the viewpoint of Information Granulation – on currently important research tracks such as social network computing, cloud computing, cyber-security, data mining, process mining, machine learning, statistics, knowledge management, AI-based systems, intelligent systems and soft computing (neural networks, fuzzy systems, evolutionary computation, rough sets, self-organizing systems), e-Intelligence (Web Intelligence, Semantic Web, Web Informatics), business intelligence, bioinformatics, medical informatics and IoT. The papers addressing how to rely on Information Granulation in the emerging field of XAI (Explainable AI) and how to use its principles to construct interpretable AI models are highly welcome as well.

    HIGHLIGHTS:
    -- The session is organized as a part of the IEEE Big Data 2021 conference (December 15-18,), which is a well-established and highly competitive international event targeted at modern trends in big data processing and analytics.

    -- The session is intended to be a forum for discussing concepts, issues, and methods by the leading researchers in the fundamental problems of Information Granulation and Granular Computing in an atmosphere promoting the exchange of ideas and viewpoints.

    -- Papers accepted to the session will be published in the IEEE Big Data 2021 conference proceedings, together with papers submitted and accepted to the main conference track.

    -- Organizers are planning a special issue on mathematical framework of big data analytics in some journal, such as e.g. Granular Computing (Springer) or Big Data Mining and Analytics (Tsinghua University Press).