[Mingli Lecture Hall, 2022 Issue 25]

  At the invitation of the School of Management and Economics, Associate Professor Wei Qiang from the School of Economics and Management of Tsinghua University came to our school for exchanges Visited and gave an academic lecture titled "Research on Machine Learning Methods for Management Explainability Enhancement - A Dynamic Multi-stage Recommendation Method Introducing the Marketing Funnel Perspective" at 10:00 a.m. on April 27, 2022 in Room 317 of the Main Building Report. The report meeting was chaired by Associate Professor Jia Lin, and many teachers and students of the college attended the report meeting.

  Professor Wei Qiang first introduced the relevant background of the online marketing industry, and pointed out that the rapid development of big data and AI has greatly promoted the digitalization of management decisions. At the same time, the incompleteness of available data in management scenarios, the subjective disturbance of output judgment, and the complexity of the internal mechanism make the "black box" phenomenon of machine learning methods in management decision-making applications more prominent (that is, insufficient interpretability). This restricts the deep application and development of machine learning methods. In view of this research background, Professor Wei and his research team proposed a recommendation method based on multi-stage dynamic Bayesian network based on the perspective of marketing funnel theory and the situational characteristics and multi-stage dynamics of consumers' online shopping. This method can model and learn the generation process of consumers' implicit psychological stage transfer and interest conversion-driven product interaction behavior. This method not only has good recommendation accuracy, but also provides a solution to detect unobservable psychological stages from consumers' observable behavior, which has better management interpretability and is beneficial to designing corresponding marketing strategies.

  After the report, the participating teachers and students had a positive and full discussion with Professor Wei and took a group photo. The report received enthusiastic response and was well received by teachers and students.

Professor Wei:

  Professor Wei Qiang is the deputy director of the Department of Management Science and Engineering, a tenured associate professor/doctoral supervisor, the deputy director of the Artificial Intelligence Management Research Center, and the deputy director of the Medical Management Research Center, School of Economics and Management, Tsinghua University. His research interests include management information systems, big data and business analysis, machine learning, intelligent recommendation, and text mining. He has published more than 40 papers in top journals in the field of management science and information systems (such as MISQ, ISR, INFORMS JoC, ACM TKDD).