Domain-Specific Knowledge Graphs - Tasks and Challenges for Next Generation Information Systems

Abstract:  

Knowledge graphs (KGs) are more and more replacing traditional information storage concepts, such as relational database systems. Due to the high diversity of application areas, a one-size-fits-all knowledge graph is not (yet) on the horizon. But domain-specific solutions are showing good results in health applications, customer support systems, and in the fashion or legal domain.

In this talk, we not only want to explore the challenges and pitfalls of creating a knowledge graph for the art domain, but also shed some light on general issues related to knowledge graphs, from named entity recognition to relation extraction and KG embeddings.

Bio: 

Ralf Krestel is Professor for Information Profiling and Retrieval at ZBW - Leibniz Information Centre for Economics and Kiel University, Germany. Prior to his appointment, he was head of the Web Science Research Group at Hasso Plattner Institute at University of Potsdam, Germany and Postdoctoral Research Fellow at University of California, Irvine, USA. In 2012, he received his Ph.D. from the University of Hannover. His research focus is on text mining, information retrieval, recommender systems, natural language processing, and machine learning. He has co-authored more than 120 peer-reviewed publications.

Host: A/Prof Gianluca Demartini

This session will be conducted in person in room 46-442 and also via Zoom: https://uqz.zoom.us/j/89362232168

About Data Science Seminar

This seminar series will be run as weekly sessions and is hosted by ITEE Data Science.