Speech Title: Algorithms for the discovery of interesting patterns in data: recent work and appliations to education
Abstract:
Intelligent systems and tools can play an important role in various domains such as for factory automation, e-business, transportation, and e-learning. The foundation of these advancements lies in the availability of high-quality data, encompassing diverse forms such as activity logs, multimedia content, and sensor-derived metrics from interactive educational environments. Managing 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 in particular educational systems.
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 such as graphs and sequences. Topics that will be discussed include high utility patterns, locally interesting patterns, periodic patterns and spatial patterns. Lastly, the SPMF open-source software will be mentioned and opportunities related to the combination of pattern mining algorithms with conventional artificial intelligence techniques to enhance the efficacy of educational intelligent systems.
Biography:
Philippe Fournier-Viger (Ph.D) is distinguished professor at Shenzhen University (China). Five years after completing his Ph.D., he came to China in 2015 and became full professor after receiving an important talent title from the National Science Foundation of China. He has published more than 400 research papers related to data mining algorithms for complex data (sequences, graphs), intelligent systems and applications, which have received more than 15,000 citations (H-Index 63 - Google Scholar). He is the founder of the popular SPMF data mining library, offering more than 250 algorithms to find patterns in data, cited in more than 1,000 research papers. He is former associate editor-in-chief of the Applied Intelligence journal and has been keynote speaker for over 30 international conferences and co-edited four books for Springer. He appears in the top 2% of researchers for scientific influence in the Stanford list, and is a Elsevier «Highly Cited Chinese Researcher» (2022). Website: http://www.philippe-fournier-viger.com.