Bridging the Gap between Text and Knowledge

Abstract

Making sense of the growing literature requires methods that will increase the speed and reliability of knowledge discovery. Moreover, due to proliferation of scientific databases and ontologies, discovery of previously unknown knowledge demands that scientists engage with many resources, covering different levels and views of (multiple) domain space in context (e.g., degree of confidence in a finding). This constitutes a major challenge in applications arising from the high complexity of mechanisms whose detailed description can only be derived from analysis of heterogeneous sources.  Natural Language Processing plays a key role in automated semantic metadata extraction, driving the extraction of structured information from unstructured documents in the form of named entities, and the fine-grained and often complex relations between them (events).  

Increasingly, it has become important not only to extract complex relations but also to capture their contextual interpretation such as degree of confidence, or certainty in a finding. 

Sophia will describe NLP methods for the extraction of structured representations from text for downstream applications while addressing challenges of information extraction tasks.

Host

Dr Guido Zuccon

Dr Guido Zuccon is an Associate Professor at the University of Queensland, Information Technology and Electrical Engineering School, an ARC DECRA Fellow (2018-2020), an Affiliate Associate Professor at the UQ Centre for Health Services Research, Faculty of Medicine, and a Visiting Principal Scientist at Queensland Health. He leads the Information Engineering Lab (ielab), a research team working in Information Retrieval and Health Data Science.

Guido's main research interests are Information Retrieval, Health Search, Formal Models of Search and Search Interaction, and Health Data Science. He has successfully attracted funding from the ARC via an ARC Discovery Early Career Research Award Fellowship and an ARC Discoverty Project. His research has also been funded by Google (Google Research Awards program), Grain Research and Development Corporation (GRDC), Microsoft (Microsoft Azure for Research Award), the CSIRO (research gifts and PhD Students Top-up scholarships), the Australian Academy of Science (FASIC program), the European Science Foundation, and Neusoft Corporation.

Speaker

Professor Sophia Ananiadou 

Sophia is a Professor of Computer Science at The University of Manchester. Her main areas of research are Natural Language Processing and Text Mining applied in Biomedicine. She is the Director of the UK National Centre for Text Mining, Deputy Director of the Institute of Data Science and AI (Manchester), Turing Fellow, ELLIS member, and Distinguished research fellow at the AI research centre (AIST Japan). Her research contributions are in information extraction, scientific discourse analysis, emotion detection,  computational terminology, for applications such as systematic reviews, semantic search, knowledge graph construction, pathway/database curation in domains such as systems biology, cancer, public health, biodiversity, and history.