Scalable and Comprehensible Visualization for Discovery of Knowledge from the Internet

We propose visualization techniques for supporting a discovery from and comprehension of the information space built on the Internet. Although the Internet is certainly a rich source of knowledge, discoveries from the net are often too hard. On the one hand, it is difficult to find places where useful knowledge is buried since the information space on the Internet are huge and ill-structured. On the other hand, even if they are found, it is still difficult to read from useful knowledge since it is scattered on a number of fine-grained pages and articles.In order to help human users to find and understand concealed knowledge, we propose two levels of visualization techniques. The first level is designed to provide scalable visualizations, presenting skeletal structures of huge hierarchies. It provides sketchy maps of the entire space and helps the user to navigate to portions where candidate information is stored. The second level provides more detailed and comprehensible views of a small region of the information space. It can help the user to understand knowledge that is scattered on multiple articles and thus inherently hard to follow.