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Professional

Track: Machine Learning

Deep Transfer Learning & Beyond: Applications of Transformer Language Models in Business Analytics

Tuesday, April 13, 2:40-3:20pm EDT

Recent progress in natural language processing involving transformer language models (TLMs) is poised to transform text analytics in organizations. This presentation will briefly review this recent progress as well as recent literature utilizing text mining in top business journals to show that suboptimal text mining techniques are prevalent and that the more advanced TLMs should be adopted by organizations. These techniques have tremendous potential for business analytics, and an overview of the large variety of high impact applications will be offered. A brief introduction to using these techniques via free cloud resources will be included. The presentation will conclude with a discussion of the potential implications of further improvements of this emerging technology on business analytics. Researchers and practitioners alike will find the unique insights of this exciting research applicable to their ongoing text analytics problems.

Richard Gruetzemacher image

Richard Gruetzemacher

Richard Gruetzemacher

Visiting Assistant Professor at the University of Memphis

The presenter is a Visiting Assistant Professor at the University of Memphis. While completing his PhD at Auburn University, he traveled to 25 leading AI conferences, speaking with and interviewing hundreds of AI experts. He has presented work on the transformative potential of AI and forecasting AI progress at the European Commission Joint Research Center, the University of Oxford and the University of Cambridge, where he spent a summer as a visiting researcher. His work on these topics has been published in Technological Forecasting and Social Change, Big Data and Cognitive Computing, the proceedings of the AAAI/ACM Conference on AI for Ethics and Society, and the proceedings of the annual Conference on Artificial General Intelligence. He has published articles applying deep learning in the Journal of the American Medical Informatics Association and the proceedings of the Americas Conference on Information Systems.