Special Sessions

Special Session 1:

Special Session on Platform for DFFT (Data Free Flow with Trust)

Special Session 2:

Special Session on Social Cognitive Computing in Digital Education and Learning

Special Session 3:

6th Special Session on Healthcare Data

Special Session 4:

Data-Driven Designation and Implementation of Automated Guided Vehicles

Special Session 5:

Privacy and Security of Big Data (PSBD 2023)

Special Session 6:

Machine Learning on Big Data (MLBD 2023)

Special Session 7:

Understanding New Markets by Data Science, Social Science, and Economics

Special Session 8:

9th Special Session on Intelligent Data Mining

Special Session 9:

9th Special Session on Information Granulation in Data Science and Scalable Computing

Special Session 1:

Special Session on Platform for DFFT (Data Free Flow with Trust)

December 15-18, 2023 Sorrento, Italy

Data is the most important property for bringing innovation and digital transformation. By using highly developed information and communication technology, we can generate, store, replicate, transfer, process and analyze data at very low cost, which realizes democratization of innovation, that is to give everyone in the world a chance for innovation. Today, the world is using the power of data to solve all kinds of issues, from global ones to everyday life ones.

Data-driven society achieves both economic development and resolution of social problems in parallel by connecting everyone and everything with each other, sharing various knowledge and information, and creating new value. From the perspective of economy, it will contribute to sustainable and harmonious economic development in the world. On the other hands, from the perspective of domestic social issues, it will contribute to the sustainability of regions and national security, including the declining birthrate, increasing aging population, depopulation of rural areas, economic disparity, and prevention of natural disasters and pandemics. For this purpose, vast Big Data in cyber space (virtual space) and physical space (real space) are linked across all over the world among various stakeholders to realize the vision of "Data Free Flow with Trust" (DFFT), which is the main topic of Digital Minister Meeting of G7 of May 2023. To establish a DFFT that spans multiple stakeholders, the openness, transparency and interoperability of data exchange must be achieved. The privacy, security, quality assurance and ease of use of the data itself must also be considered.

The general purpose of this special session in IEEE BigData 2023 conference is to bring together researchers, academicians, and sector employees from different fields and disciplines and to exchange information on their practical activities, research, ideas and findings about global platform for DFFT. It is also aimed to encourage debate on how global platform can effectively support big data distribution, sharing, and application in terms of infrastructure, technology, governance, business, and so on, and to develop a common understanding for research conducted in this multidisciplinary field.

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

• Global Data Space Platform
• Federated Data Platform
• Federated Data Catalog
• Supply Chain Data Management
• Data Platform Federation Technology
• • Connector and Broker Technology
  • Data Collection Technology
  • Fediverse
  • Trust Federation
• Data Business Platform
• Data Trading Market
• Data Processing Platform
• DWH (Data Warehouse) Platform
• Data Lake Platform
• ETL (Extract, Transform, Load) Platform
• IoT Realtime Data Collection Platform
• Open Source Data Processing Platform
• Secure Data Sharing/Processing Platform
• Data Platform with Secure Multiparty Computation
• Federated Learning Platform
• Blockchain-based Data Platform
• Trusted Web Platform
• DIDs: Decentralized Identifiers
• Data Governance Rules, Law, and Policy
• Cross-Border Data Flow Policy
• Personal Data and Privacy Protection
• Industry Confidential Data Protection
• Data Sharing Applications
• Smart City
• Digital Government
• Smart Mobility, MaaS (Mobility as a Services)
• Disaster Prevention and Response
• Supply Chain Management
• Carbon Neutral, CO2 Calculation, CO2 Proof
• Geographical Information Management
• Information Bank

Session Organizers
Noboru Koshizuka (Chair)
Interfaculty Initiative in Information Studies
The University of Tokyo
noboru@koshizuka-lab.org

Stephan Haller
Institute for Public Sector Transformation
Bern University of Applied Sciences
stephan.haller@bfh.ch

Hiroshi Mano
Data Society Alliance
h.mano@data-society-alliance.org

Takashi Michikata
Interfaculty Initiative in Information Studies
The University of Tokyo
takashi.michikata@koshizuka-lab.org

Yukio Ohsawa
Department of Systems Innovation,School of Engineering,
The University of Tokyo
ohsawa@sys.t.u-tokyo.ac.jp

Boris Otto
Fraunhofer ISST
Boris.Otto@isst.fraunhofer.de

Shinji Shimojo
Cybermedia Center,
Osaka University
shinji.shimojo.cmc@osaka-u.ac.jp

Hideaki Takeda
National Institute of Informatics
takeda@nii.ac.jp

Important Dates

• Full paper submission: Oct 2 (Mon), 2023
• Notification of paper acceptance: Nov 3, 2023
• Camera-ready of accepted papers: Nov 17, 2023
• Conference: Dec 15-18, 2023

Instructions
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website https://bigdataieee.org/BigData2023/CallPapers.html).
Accepted papers will be published in the conference proceedings.
All accepted papers must be presented by one of the authors in the conference to include the article in the proceedings.
If you have any questions about the special session, please do not hesitate to contact us.
Paper submission page:

Special Session 3:

6th Special Session on HealthCare Data in IEEE Big Data 2023

December 15-18, 2023 Sorrento, Italy

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 2023 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

Special Session Organizers:
Sultan Turhan (sturhan@gsu.edu.tr), PhD., Department of Computer Engineering, Galatasaray University
Assist. Prof. Ozgun Pinarer (opinarer@gsu.edu.tr), Department of Computer Engineering, Galatasaray University

Important Dates:
Full paper submission: Sep 24, 2023
Notification of paper acceptance: Oct 15, 2023
Camera-ready of accepted papers: Nov 15, 2023
Conference: Dec 15-18, 2023

Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website (https://bigdataieee.org/BigData2023/CallPapers.html).
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.
If you have any questions about the special session, please do not hesitate to contact us.

Special Session 4:

Data-Driven Designation and Implementation of Automated Guided Vehicles

December 15-18, 2023 Sorrento, Italy

Special Session Organizer
Jerry Chun-Wei Lin
Western Norway University of Applied Sciences, Norway

Francesco Piccialli
University of Naples Federico II, Italy

Gautam Srivastava
Brandon University, Brandon, Canada

Rafał Cupek
Silesian University of Technology, Poland

Dariusz Mrozek
Silesian University of Technology, Poland

Brief Description and Justification
The growing popularity of Autonomous Guided Vehicles (AGVs) has not only been the result of their technical features but also their ability to cooperate. Cooperative-based internal logistics enables increased production flexibility. AGVs have become a key enabling technology for the flexible internal logistics that are required for agile production systems. Modern production systems are characterized by frequent changes that result from orders that are changed by customers, low material buffers, the agile production technologies that are performed by robotized production stands and the many variants of production technology that can be used. All of the above-mentioned factors require the production process to be supported online by highly advanced information services, which are performed during successive steps in the production chain. In addition, big and remote sensing data play a fundamental role in AGV, which helps acquire the patterns of driving/travel behaviour, human mobility, and traffic flow, and in sensing a more large-scale environment and giving more accurate, traffic-aware navigation. This means that the production activities cannot be centrally planned but have to be performed cooperatively concerning the sensing data, ongoing production tasks, available materials, production equipment and technologies. The new generation of data-driven systems in AGVs has to support the autonomy and distribution of decision-making processes.

Thus, this special session is focused on the following issues but not limited to:
• Data Mining support for Energy and Resource Efficient Internal Logistics
• Communication between Automated Guided Vehicles and Production Stands and Production System
• Automated Guided Vehicle Integrated with Collaborative Robot
• Use Case-based CoBotAGVs Integration with Industry4.0 Production Systems
• Multi-source sensor data collection, processing and data fusion by collaborative AGV
• Machine learning-based traffic safety analysis, trajectory and route prediction
• Data-driven autonomous driving assistance
• Prediction of traffic flow based on sensing data of AGVs
• Pavement performance evaluation and predictions of AGVs
• Architecture design, implementation and case studies of AGVs

Important Dates
Full paper submission: 1 Nov 2023
Notification of paper acceptance: 15 Nov 2023
Camera-ready of accepted papers: 22 Nov 2023
Conference: Dec 15-18, 2023

Instructions
Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found on the conference website https://bigdataieee.org/BigData2023/CallPapers.html).
Accepted papers will be published in the conference proceedings.
All accepted papers must be presented by one of the authors in the conference to include the article in the proceedings.
If you have any question about the special session, please do not hesitate to contact us.

Paper submission page: Link

Special Session 5:

Privacy and Security of Big Data (PSBD 2023)

December 15-18, 2023 Sorrento, Italy

Best Papers of PSBD 2023 will be Invited for Extended Submission to a Top-Quality Journal

Aim and Scope
The 10th IEEE Special Session “Privacy and Security of Big Data” (PSBD 2023) of the 2023 IEEE International Conference on Big Data (IEEE BigData 2023) follows the great success of nine 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 2023 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 10th IEEE Special Session on “Privacy and Security of Big Data” (PSBD 2023) of the 2023 IEEE International Conference on Big Data (BigData 2023) will be held in Sorrento, Italy, during December 15-18, 2023, and it aims to synergistically connect the research community and industry practitioners. It provides an international forum where scientific domain experts and Privacy and Security researchers, practitioners and developers can share their findings in theoretical foundations, current methodologies, and practical experiences on Privacy and Security of Big Data. PSBD 2023 will provide a stimulating environment to encourage discussion, fellowship, and exchange of ideas in all aspects of research related to Privacy and Security of 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 PSBD 2023 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 Privacy and Security of Big Data, and additionally to continue on the success of the event across future years.

Special Session Location
Sorrento, Italy

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: 6 pages

Demo Papers: 6 pages

Position Papers: 6 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 Privacy and Security of Big Data”.

Paper Publication
Accepted papers will appear in the official IEEE Big Data 2023 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: September 27, 2023
Notification of acceptance: October 27, 2023
Camera-ready paper due: November 17, 2023
Special Session: December 15-18, 2023

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 6:

8th IEEE Special Session on Machine Learning on Big Data (MLBD 2023)

December 15-18, 2023 Sorrento, Italy

Best Papers of MLBD 2023 will be Invited for Extended Submission to a Top-Quality Journal

Aim and Scope
The 8th IEEE Special Session “Machine Learning on Big Data” (MLBD 2023) of the 2023 IEEE International Conference on Big Data (IEEE BigData 2023) follows the great success of seven 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 stirred-up 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-to-doctor, 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) machine-learning-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 2023 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 8th IEEE Special Session “Machine Learning on Big Data” (MLBD 2023) of the 2023 IEEE International Conference on Big Data (IEEE BigData 2023) will be held in Sorrento, Italy, during December 15-18, 2023, 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 2023 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 2023 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
Sorrento, Italy

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: 6 pages

Demo Papers: 6 pages

Position Papers: 6 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 2023 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: September 27, 2023
Notification of acceptance: October 27, 2023
Camera-ready paper due: November 17, 2023
Special Session: December 15-18, 2023

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 7:

Understanding New Markets by Data Science, Social Science, and Economics

December 15-18, 2023 Sorrento, Italy

Link to the special session: https://tetsuwaka.net/UNMDSSSE2023/

Recent innovations with Big Data and Artificial Intelligence have created new markets and dramatically increased the importance of data. Despite these social changes, existing economics, market design, management, information systems, engineering, social science, and data science approaches to these new social issues have limitations. New market understanding schemes and solutions for social implementation are needed.

To address these gaps, we propose a special session named “Understanding New Markets by Data Science, Social Science, and Economics” to discuss the processes and interactions among data, humans, and society with researchers from engineering, information systems, data science, social science, management, and economics. The topics to be covered in this session are practical issues for understanding new societies and markets, including analytical work with data and solutions to complex social problems. The session will cover not only cleanly formatted, homogeneous data but also heterogeneous data that influence human behavior, thinking, and intentions across different domains. Discussions will focus on how large-scale data can be used in healthcare, business management, and public systems, as well as discussions of quantitative assessments of what works in these areas and the obstacles to advancing their use. In addition to these research areas, we will explore utilizing large-scale data and designing mechanisms and institutions that consider social and cultural backgrounds across disciplines. We believe that this special session focusing on the new schemes for market understanding and design will be of great significance to academia and society.

We call for anyone interested in the following topics related to this special session:

Data-oriented Application Areas:

• Statistical Graphics and Mathematics
• Financial Security, and Business
• Physical Sciences and Engineering
• Earth, Space, and Environmental Sciences
• Text, Documents, and Software
• Social, Ambient, and Information Sciences
• Multimedia (Image/Video/Music) Mining

Case Studies on Data Exchange and Collaboration:

• Methods for Data Evaluation and Utilization
• Data Management and Curation
• Risks, Limitations, and Challenges of Data Exchange
• Trust, Resilience, Privacy, and Security Issues
• Design of Data

Data-focused Cognitive Research:

• Human-Computer Interaction
• Behavioral Science and Modeling (quantitative and qualitative approaches)
• Theoretical Models and Experimental Methods in Human-Computer Interaction
• Subjects and Field Experiments
• Cognitive Science and Human Behavior

Empirical and Comprehension Focused Data Utilization:

• Modeling of Machine Learning for Social Data
• Ontology and Dictionary
• Business Efficiency
• Cognition and Perception Issues
• Natural Language Processing, and Text Mining
• Retrieval/recommender systems

Data Market:

• Process and Technologies for Data Exchange
• Representation of Knowledge and Requirements
• Pricing and Evaluating Mechanism of Data
• Design of Data Platform
• Data Acquisition and Sensors
• Strategic Manipulation and Incentives
• Fairness and Social Welfare

NLP in Social Science:

• Practical Text Mining
• Financial/Economic Natural Language Processing
• Summarization
• Topic Analysis
• Report Generation
• Large Language Model for Social Science

Format and Schedule

Time	Contents
9:00-12:00	General Presentations (5 presentations)
12:00-14:00	Lunch Break
14:00-15:00	Invited Talk
15:00-18:00	General Presentations (5 presentations)
18:00-	Social Gathering

Organizers

Teruaki Hayashi, University of Tokyo, Japan (Co-chair)
Hiroki Sakaji, University of Tokyo, Japan (Co-chair)
Naoki Watanabe, Keio University, Japan (Co-chair)

Special Session 8:

9th Special Session on Intelligent Data Mining

December 15-18, 2023 Sorrento, Italy

After the successes of the first, second, third, fourth, fifth, sixth, seventh and eight 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), Online Pandemic Session (2021); Osaka, JAPAN (2022) and the 9th Special Session on Intelligent Data Mining in Sorrento, ITALY (2023) 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
• GPU Applications
• Medical Imaging
• Deep Learning
• Scalable Computing, Cloud Computing
• Knowledge Discovery, Integration, Transformatio
• Information Retrieval
• Information Security
• 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 in Data Mining
• Future Directions and Challenges in Data Mining
• Industrial Challenges in Data Mining
• Demo Applications in Data Mining

Papers should be submitted for this special session by Sept 17, 2023

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/BigData2023/).

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
Gazi University, Turkey

The important dates for this special session are:

• Full Paper Submission Deadline : Sept 17, 2023 11:59 pm PST
• Notification of Acceptance : Nov 5, 2023
• Camera-ready papers & Pre-registration : Nov 17, 2023, 11:59pm PST
• Conference Dates : Dec 15-18, 2023

Special Session 9:

9th Special Session on Information Granulation in Data Science and Scalable Computing

December 15-18, 2023 Sorrento, Italy

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 diverse data and associated domain knowledge. Information Granulation, under different names, has appeared in many fields, such as granularity in artificial intelligence, divide and conquer methods for scaling calculations, approximate computing, knowledge representation, topological data analysis, image processing 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 the humans and AI. Herein we may follow the phrase "Information Granules = Fundamental Pieces of Human Knowledge" and treat Granular Computing as one of important meta-mathematical methodologies for Big Data Analytics.

SESSION SCOPE:
The 9th session in this series continues to address the theory and practice of derivations and computations based on various types of granular models and structures. It provides researchers from both academia and industry with the means to present the state-of-the-art results and methodologies related to Information Granulation and Granular Computing, with a special emphasis on applications in Data Science and Scalable Computing. The session also refers – from the particular viewpoint of Information Granulation – to 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, soft computing, e-Intelligence, business intelligence, bioinformatics, health informatics and IoT. The papers addressing Information Granulation in the emerging field of XAI and using its principles to construct interpretable AI models are highly welcome as well. Particularly, we encourage the papers which deliver experimental results but in the same time, provide theoretical foundations to justify those results.

HIGHLIGHTS:

• The session is organized as a part of the IEEE Big Data 2023 conference (December 15-18), which is a well-established and competitive international event targeted at modern trends in big data processing and analytics.
• The session is intended to be a forum for discussing ideas, issues and methods based on and inspired by Information Granulation and Granular Computing, in an atmosphere promoting free exchange of viewpoints and perspectives coming from different application areas.
• Papers accepted to the session will be published in the IEEE Big Data 2023 conference proceedings, together with papers accepted to the main conference track.
• Organizers are planning a special issue in a relevant scientific journal, such as Big Data Research (Elsevier), Granular Computing (Springer) or Big Data Mining and Analytics (Tsinghua University Press).
• Organizers particularly encourage papers which deliver experimental results but in the same time, provide theoretical foundations to justify those results.

ORGANIZERS

• Shusaku Tsumoto
  Shimane University, Japan
  tsumoto@med.shimane-u.ac.jp
  
• Dominik Slezak
  University of Warsaw & QED Software, Poland
  dominik.slezak@qed.pl
  
• Tzung-Pei Hong
  National University of Kaohsiung, Taiwan
  tphong@nuk.edu.tw
  
• Weiping Ding
  Nantong University, China
  dwp9988@hotmail.com
  

IMPORTANT DATES
Full paper submission: October 15, 2023
Notification of paper acceptance: November 8, 2023
Camera-ready of accepted papers: November 22, 2023
Conference: December 15-18, 2023