Methods for finding information in massive amounts of text are well established, and run in the background of familiar Web search engines such as Google. The next challenge is to find a way to help experts and analysts in a given field to tap the tacit knowledge hidden in masses of text; not just to find the needle in the haystack, but to understand how it relates to other complex issues, to make sense of the data on a higher level, and to reveal what needles they should be looking for in the first place.
The proposed research aims to bring together text mining, text visualization and human computer interaction to create computer tools to support the sense-making activity of the human user. Key challenges include:
- the extraction and visualization of concepts, names and relations from large noisy text corpora;
- visualization of relations between concepts in text as graph structures;
- support for real-time visualization and interaction, which requires a careful trade-off between off-line and on-line processing;
- novel text visualization techniques and interaction techniques that permit the domain analyst to browse through the knowledge content of the text corpus and fine tune the text mining, without becoming a text mining expert.