I am a PhD student in the Natural Language Processing and Text Mining group. My research focuses on how to summarise medical arguments in social media.
Argument mining is an exciting new field that could have far-reaching implications for fact-checking, decision-making, marketing, legal judgements and more. However, due to its meticulous and logical nature, it is still an open challenge to summarise a large number of arguments effectively. The Knowledge Graph, because of its inherent strengths, allows for the incorporation of rich common knowledge and contextual content into the model. This offers the possibility to assess the quality of arguments and to produce high-quality summaries of arguments.
My research will focus on how argument knowledge graphs can be used to guide the generation of high-quality arguments and the design of automated evaluation methods to advance the field of argumentation mining.