Effective techniques of combining information visualization with natural language processing

In this thesis, we present three research projects that lie on the intersection of visual analysis and natural language processing (NLP) covering a very broad range of user information needs and analytical tasks. On one hand, integrating NLP techniques into visual frameworks can facilitate the exploration and analysis of large-scale textual data. In this domain, we present ConVIScope, a visual framework designed for exploring patient-doctor conversations. On the other hand, visual analytics can also assist in the development of NLP models by providing them with valuable insights about the model's intrinsic properties and behaviours. Under this line of research, we propose T³-Vis, a system that utilizes visual analytics to assist the users in the training of Transformers, a dominant architecture in NLP. Lastly, we present an in-depth case study where we used a novel pipeline for analyzing and improving extractive summarization models with guidance from our visual interface, T³-Vis.Science, Faculty ofComputer Science, Department ofGraduat