Upcoming Invited Talks in April

the LUH|AI invites you to the upcoming Invited Talks:

Talk 1/2


Dr. Jennifer D'Souza

Leibniz Information Centre for Science and Technology University Library



Time and location

April 20, 16:00, 3408-1630 (Appelstr. 9A)



Semantic Publishing of Scientific Contributions in the Open Research Knowledge Graph



The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based - formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this talk, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.

Talk 2/2


Assist.-Prof. Dr. Joonsuk Park

University of Richmond, VA, USA



Time and location

Tuesday, April 25, 17:00, 3403-A141 (Appelstr. 11)



Evaluative Argument Mining and Its Applications



The ease of internet access has significantly increased the number of user comments authored by inexperienced writers. Despite the potential usefulness of such comments, readers face the daunting task of sifting through copious amounts of uninformative content to extract relevant information. One popular approach to deal with this problem is to build systems that can help the readers by recommending well-written comments or summarizing available information. We, however, consider the problem from the perspective of the commenters: Can we build a system that can guide the commenters to write “better” comments? Such an approach would enhance the overall quality of textual content online and complement existing solutions for reader assistance.

In this talk, I will present the core components of an automated system to assist commenters in constructing better-structured arguments in their comments. These include: (1) A monological argumentation model to capture the evaluability of arguments in the online setting, (2) A classifier for determining an appropriate type of support (either reason or evidence) for propositions comprising user comments, (3) A classifier for identifying support relations present in user comments. I will also discuss how this system can be applied to practical applications such as assistive commenting interfaces and recommendation systems.



Joonsuk Park is an assistant professor in the Department of Computer Science, also affiliated with the Linguistics Program, at the University of Richmond. Currently, he is a visiting scholar at NAVER AI Lab. His research interests primarily lie in argument mining, fact verification and ethics, with publications at major NLP conferences such as ACL, EMNLP, and NAACL. He has also won several grants and awards, including the Jeffress Trust Awards Program in Interdisciplinary Research.

External participants (i.e. neither students nor employees of LUH) are kindly requested to send a short, informal email to office@ai.uni-hannover.de to register.