Prof. Thomas Hanne
University of Applied Sciences and Arts Northwestern Switzerland, Switzerland

Title:

Using Artificial Intelligence and Text Mining for Business Innovation 

Abstract:

We reflects on the business innovation supported by developing software solutions based on text mining, natural language processing, and artificial intelligence techniques to meet the business needs communicated by Swiss companies. Four related projects from different industries and with different challenges are discussed in order to identify common procedures and methodologies that can be used. One of the partners, in the gig work sector, offers a platform solution for employee recruitment for temporary work. The work assessment is performed using short reviews for which a method for sentiment assessment based on machine learning has been developed. Another partner, in the financial advice sector, operates an information extraction service for business documents, including insurance policies. This requires automation in the extraction of structured information from pdf-files. The other two projects are in the railway industry and in the healthcare sector.  The common path to innovation in such projects includes business process modeling and the implementation of novel technological solutions such as natural language processing and machine learning.

Keywords — Machine Learning, Natural Language Processing, Text Mining, Digitalization, Business Process Management, Business Innovation 

Biography:

Thomas Hanne received master's degrees in Economics and Computer Science, and a PhD in Economics. From 1999 to 2007 he worked at the Fraunhofer Institute for Industrial Mathematics (ITWM) as senior scientist. Since then he is Professor for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland and Head of the Competence Center Systems Engineering since 2012. 

Thomas Hanne is author of more than 180 journal articles, conference papers, and other publications and editor of several journals and special issues. His current research interests include computational intelligence, evolutionary algorithms, metaheuristics, optimization, simulation, multicriteria decision analysis, natural language processing, machine learning, systems engineering, software development, logistics, and supply chain management.