Exploring Scientific Literature Search through Topic Models.

With the fast growing amount of scientific literature, browsing through it can be a dicult task: formulating a precise query may be problematic as new research areas emerge quickly and different terms are often used to describe the same concept. To tackle some of these issues, we built a system for exploratory scientific search based on topic models. An initial short user study shows that through visualizing the relationship between keyphrases, documents and authors, the system allows the user to better explore the document search space compared to traditional systems based solely on search query.