EKAW 2024

Keynote Speakers

EKAW 2024 is honored to present a series of keynote addresses by distinguished experts in Knowledge Engineering and Knowledge Management.

Our keynote speakers will share insights on critical developments in our field, including the integration of Language Models with symbolic representations, advancements in knowledge base technologies, and emerging applications in various domains. These presentations will offer valuable perspectives on current challenges and future directions in knowledge engineering, fostering intellectual discourse and potential collaborations.

Additional keynote speakers will be announced in due course. We encourage you to check back for updates.

Keynote Speaker
A hitchhiker's guide to Ontology
Fabian M. Suchanek
Fabian M. Suchanek
Télécom Paris University
Keynote Speaker
Is the Search Engine of the Future a Chatbot?
Suzan Verberne
Suzan Verberne
Leiden University

Fabian M. Suchanek

Fabian M. Suchanek

A hitchhiker’s guide to Ontology

Bio: Professor Fabian M. Suchanek is a leading researcher in the field of knowledge extraction and knowledge bases. His work bridges the gap between natural language processing and symbolic representations, with significant contributions to the development of large-scale knowledge bases.

Abstract: Language Models have brought major breakthroughs in natural language processing. Notwithstanding this success, I will show that certain applications still need symbolic representations. I will then show how different methods (language models and others) can be harnessed to build such symbolic representations. I will also introduce our main project in this direction, the YAGO knowledge base. I will then talk about the incompleteness of knowledge bases. We have developed several techniques to estimate how much data is missing in a knowledge base, as well as rule mining methods to derive that data. I will then present our work on efficient querying of knowledge bases. Finally, I will talk about applications of knowledge bases in the domain of speech analysis and the digital humanities, as well as about our methods for explainable AI.

Suzan Verberne

Suzan Verberne

Is the Search Engine of the Future a Chatbot?

Bio: Suzan Verberne is a Natural Language Processing professor at Leiden University. She earned her PhD in Question Answering in 2010 and specializes in NLP and Information Retrieval. Her work spans various domains, focusing on interactive information access for specific fields and low-resource contexts. She's particularly interested in search engines and large language models. Verberne is active in NLP and IR communities, holding leadership roles in major conferences and promoting diversity.

Abstract: The rise of Large Language Models (LLMs) has had a huge impact on the interaction of users with information. Many people argue that the age of search engines as we know them has ended, while other people argue that retrieval technology is more relevant than ever before, because we need information to be grounded in sources. In my talk I will argue that both statements are true. I will discuss the multiple relations between LLMs and Information Retrieval: how can they strengthen each other, what are the challenges we face, and what directions should we go in our research? Specifically, I will go into the role of the human in the interaction with information: what is the role of domain experts and what can domain knowledge contribute to the development of interactive search systems?