第六届机器学习、大数据与商务智能国际会议

About MLBDBI 2024

Welcome to the official website of 2024 6th International Conference on Machine Learning Big Data and Business Intelligence （MLBDBI 2024）.

2024 6th International Conference on Machine Learning Big Data and Business Intelligence （MLBDBI 2024） will be held on November 1-3 2024 in Hangzhou China. The idea of the conference is for the scientists scholars engineers and students from the Universities all around the world and the industry to present ongoing research activities and hence to foster research relations between the Universities and the industry.

The conference will be held every year to make it an ideal platform for people to share views and experiences in Machine Learning Big Data and Business Intelligence and related areas. It will bring you an unexpected harvest. We sincerely welcome you to be a member of MLBDBI 2024.

Important Dates

Full Paper Submission Date

August 15 2024

Registration Deadline

September 15 2024

Final Paper Submission Date

September 30 2024

Conference Dates

November 1-3 2024

Speakers

Professor Jiangtao Qiu

Southwestern University of Finance and Economics China

Dr. Jiangtao Qiu is a professor and doctoral supervisor at the School of Computing and AI at Southwestern University of Finance and Economics. His research interests include data mining business intelligence and FinTech. In the last ten years he has published more than four papers; presided over one natural science foundation in China; conducted two ministry of education research projects; as well as edited three textbooks.

Speech title: Business Intelligence: A perspective of Users in E-commerce

Abstract: The term “business intelligence“ can be traced back to the 1980s; however it was not until Microsoft introduced its OLAP Service product in 2000 that “business intelligence“ started gaining widespread attention in both industry and academia. During this period business intelligence primarily focused on multidimensional data analysis and automated reporting technology within data warehouses. Over the course of more than two decades of evolution and development particularly with the rise of e-commerce and continuous advancements in artificial intelligence technology the concept and research scope of business intelligence have significantly expanded beyond its initial scope of data analysis. This report takes an e-commerce user perspective to provide a comprehensive and thorough review of the theoretical framework underlying business intelligence. It integrates recent significant research findings from deep learning technology in this field while systematically examining the progress made in academic research on business intelligence from an e-commerce user standpoint. Furthermore it offers prospective discussions on future trends and directions for its development.

Professor Tong Li

Shenzhen University China

Dr. Tong Li male professor of the College of Management the executive director of Institute of Mobile-Internet-Things Industrialization of Shenzhen University. An expert in the database of experts in philosophy and social sciences of Guangdong Province an expert of the Shenzhen Science and Technology Innovation Commission. A bachelor‘s degree in mathematics from Hubei Normal University a master‘s degree and a PhD degree in system engineering from Huazhong University of Science and Technology. Dr. Li once taught at Wuhan University of Technology and Huazhong University of Science and Technology. As a science and technology envoy participated in the operation and research and development of enterprises and once served as the Director of the research and development center of Compaq （HP） Scipower E-commerce the Assistant to the chairman of Scipower Electronics and the Director of the the Emoticon Recognition Innovation Application Joint Laboratory of National Supercomputing Shenzhen Center & Shenzhen Zhihuilin Network Technology Co. Ltd.

Speech title: Mortal Computation

Abstract: Mortal Computation refers to a novel computational paradigm proposed by Hinton. It emphasizes a closer integration between software and hardware drawing inspiration from the characteristics and principles of biological intelligence. The goal of Mortal Computation is to address energy consumption issues by mimicking the energy-efficient information processing capabilities of biological systems. The idea of Mortal Computation is introduced in this keynote. The possibilities and challenges of its realization will be discussed.

Call For Papers

The topics of interest include but are not limited to:

Machine Learning

· Deep and Reinforcement learning

· Pattern recognition and classification for networks

· Machine learning for network slicing optimization

· Machine learning for 5G system

· Machine learning for user behavior prediction

· New innovative machine learning methods

· Optimization of machine learning methods

· Performance analysis of machine learning algorithms

· Experimental evaluations of machine learning

· Data mining in heterogeneous networks

· Machine learning for multimedia

· Machine learning for Internet of Things

· Machine learning for security and protection

· Distributed and decentralized machine learning algorithms

Big Data

· Big Data Analytics

· Data Science Models and Approaches

· Algorithms for Big Data

· Big Data Search and Information Retrieval Techniques

· Big Data Acquisition Integration Cleaning and Best Practices

· Big Data and Deep Learning

· Scalable Computing Models Theories and Algorithms

· In-Memory Systems and Platforms for Big Data Analytics

· Big Data and High Performance Computing

· Cyber-Infrastructure for Big Data

· Performance Evaluation Reports for Big Data Systems

· Storage Systems （including file systems NoSQL and RDBMS）

· Resource Management Approaches for Big Data Systems

· Many-Core Computing and Accelerators

· Big Data Applications for Internet of Things

· Mobile Applications of Big Data

· Big Data Applications for Smart City

· Data Streaming Applications

· Fault Tolerance and Reliability

· Scalability of Big Data Systems

· Big Data Privacy and Security

· Big Data Archival and Preservation

· Visual Analytics Algorithms and Foundations

· Graph and Context Models for Visualization

· Big Data Transformation and Presentation

Business Intelligence

· Intelligent Computing Methodologies and Applications

· Evolutionary Computing and Learning

· Swarm Intelligence and Optimization

· Signal Processing and Pattern Recognition

· Image Processing and Information Security

· Virtual Reality and Human-Computer Interaction

· Business Intelligence and Multimedia Technology

· Healthcare Informatics Theory and Methods

· Natural Language Processing and Computingal Linguistics

· Intelligent Computing in Robotics

· Intelligent Control and Automation

· Intelligent Data Fusion

· Intelligent Agent and Web Applications

· Intelligent Fault Diagnosis

· Intelligent cloud-support communications

· Intelligent ressource allocation

· Intelligent energy-aware/green communications

· Intelligent software defined networks

· Intelligent positioning and navigation systems

· Intelligent wireless communications

· Intelligent wireless sensor networks

Publication

All papers submitted to MLBDBI 2024 will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process all accepted papers will be published in the Conference Proceedings and submitted to EI Compendex Scopus for indexing.

Note: All submitted articles should report original results experimental or theoretical not previously published or being under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academic. Hence any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.