Topic: Research on Data Mining and Learning Strategies for Business Big Data

Lecturer: Professor Li Minqiang ---- Tianjin University

Moderator: Professor Kou Gang ---- School of Business Administration

Time: Dec. 2nd, 2020.   13:00-14:30 (UTC+8)

Live Broadcast Via Tencent Meeting ID: 934 876 448

   (International Platform: VOOV Meeting ID: 934 876 448)

Host: School of Business Administration, SWUFE Scientific Research Department

About the Lecturer:

Li Minqiang,professor of School of Management and Economics, Tianjin University, doctoral supervisor, winner of the National Science Foundation for Distinguished Young Scholars.His main research fields include information management and e-commerce, information products and information services, data mining and business intelligence, evolutionary computing theory and applications.Academic papers presented at MIS Quarterly, IEEE Transactions on Neural Networks and Learning Systems, Journal of Management Information Systems, Pattern Recognition, European Journal of Operational Research,Journal of Evolutionary Economics, Journal of Management Science, Journal of Systems Engineering, ICIS, PACIS and other important academic journals and conferences at home and abroad.He won the second prize of the National Science and Technology Progress Award, the first prize of the Science and Technology Progress Award of the Ministry of Education, the first prize of the Science and Technology Progress Award of Chinese Institutions of Higher Learning (in the category of natural science), and the Science and Technology Progress Award of Tianjin City.

About the Lecture:

With the in-depth development of new informationization such as networking, digitalization and intelligentization, as well as the innovation and popularization of the new generation of information and communication technology, the quality and efficiency of management decisions in business activities have been greatly improved.This report focuses on the characteristics and connotation of the concept of business big data, analyzes the value of business big data technology from the perspective of epistemology and methodology, and summarizes the strategies of business big data mining, this paper presents a framework of data fusion, Information Fusion, Knowledge Fusion, subspace and ensemble learning for demand-based big data analysis, and analyzes the essential features and general framework of big data mining and machine learning, this paper introduces a typical data mining and learning Algorithm based on subspace and ensemble learning.Finally, this paper introduces the case of integrated learning technology solution of the subspace of the Internet personal credit service platform system based on the business model of the Internet personal credit service platform.