Pattern Mining: Principles, Applications, and Future Directions
Pattern mining is a core area in data mining. In this talk, I will review my work on pattern mining in the last 20 years. I will focus on three interleaving main lines, technical principles, data variety, and new application challenges. I will illustrate how the advances in pattern mining empower new progress in some other areas, such as data warehouses, information retrieval, and network science. Moreover, I will demonstrate how pattern mining research produced visible impact on industrial practice. Last, I will present several attractive challenges and opportunities for pattern mining in the era of AI and data science.
Jian Pei’s professional interest is to facilitate efficient, fair, and sustainable usage of data for social, commercial and ecological good. Through inventing, implementing and deploying a series of data mining principles and methods, he produced remarkable values to academia and industry. His algorithms have been adopted by industry, open source toolkits and textbooks. His publications have been cited over 87,000 times. He is also an active and productive volunteer for professional community services, such as chairing ACM SIGKDD, running many premier academic conferences in his areas, and being editor-in-chief or associate editor for the flagship journals in his fields. His academic accomplishments have been acknowledged by the Royal Society of Canada Fellowship, ACM Fellowship, IEEE Fellowship, ACM SIGKDD Innovation Award, ACM SIGKDD Service Award, influential paper awards, best paper awards, and several other prestigious awards. Currently he is a full professor at Simon Fraser University.