A. Prof. Dimitrios A. Karras, National and Kapodistrian University of Athens (NKUA), Greece
Research Area: intelligent & distributed systems, multiagent systems, pattern recognition and computational intelligence, image & signal processing/systems, biomedical systems, communications and networking as well as security and sustainability applications
Title: On Artificial Intelligence and Data Science Impact on business and economic growth resilience towards sustainability
This speech aims at presenting the major application areas and practices of AI and Data Science along with their implications, recent trends and market perspectives in business and economy. It will be focused on the emergent data economy integrating 4th Industrial Revolution and Big Data analytics results into providing new emerging services in all fields of the public and private sector of economy. Moreover policy and ethical issues in the use of AI and Data Processing / Automation will be discussed along with their implications and constraints imposed in business and economic evolution. Finally, the impacts of 4th Industrial Revolution technologies of AI/Robotics as well as those of the emergent Data Economy will be briefly analysed in terms of sustainability in business and economy growth.
Prof. Philippe Fournier-Viger, Shenzhen University, China
Research Area: Data Mining, Pattern Mining, Graphs, Sequences, Prediction, Big Data, Artificial Intelligence
Title: Advances and challenges for the automatic discovery of interesting patterns in data
Intelligent systems and tools can play an important role in various domains such as for factory automation, e-business, and software engineering. To build intelligent systems and tools, high-quality data is generally required. Moreover, these systems need to process complex data and can yield large amounts of data such usage logs, images, videos, and data collected from sensors. Managing the data to gain insights and improve these systems is thus a key challenge. It is also desirable to be able to extract information or models from data that are easily understandable by humans. Based on these objectives, this talk will discuss the use of data mining algorithms for discovering interesting and useful patterns in data generated from intelligent systems and other applications.
The talk will first briefly review early study on designing algorithms for identifying frequent patterns. Then, an overview of recent challenges and advances will be presented to identify other types of interesting patterns in more complex data. Topics that will be discussed include high utility patterns, locally interesting patterns, and periodic patterns. Lastly, the SPMF open-source software will be mentioned and opportunities related to the combination of pattern mining algorithms with traditional artificial intelligence techniques for intelligent systems will be discussed.
Prof. Jie Tang, Guangzhou College of Technology and Business, China
Title: The Spatial Effect of Digital Economy on Port-city coordinated Development
This presentation discusses the spatial effects of digital economy in promoting the development of port-city coordination. Theoretically, the digital economy can promote the development of port-city coordination by improving the logistics efficiency of the port, the cross-border trade environment, and the high-quality development of the port hinterland cities. Moreover, its impact path is characterized by Internet communication which bears significant spatial features. The spatial effects are analyzed through spatial econometrics techniques. Specifically, the comprehensive development levels of digital economy, and the port city synergy degrees of 13 port cities in Guangdong from 2011 to 2019 are calculated, and a dynamic spatial Durbin model is constructed based on the calculation. The results show that the digital economy has a positive spatial spillover effect on the port-city coordination. This presentation provides a new research perspective of space and regional integration, for the port-city coordination under the circumstances of digital economy development.
2022 International Conference on Computer Science, Information Engineering and Digital Economy (CSIEDE 2022) http://csiede.org/