Semantic approach to visualization of research front of scientific papers using web-based 3D graphic

In this paper we describe a semantic approach to visualization of 3D cyberspace of scientific papers and their research front using web-based 3D graphic. The most cited and significant documents in this cyberspace are represented by spheres of a large size and the distance between documents is proportional to their semantic similarity. A new measure of semantic similarity of documents is proposed that is determined by the maximum correlation between explicit and implicit connectivity of the documents. A new science contextual citation index (SCCI) that is defined by a correlation maximum with a science citation index (SCI) is proposed and implemented. SCCI can more accurately measure scientific impact, find significant documents and evaluate new articles with zero SCI. Significant similar articles confirm each other and form clusters in the cyberspace. Research front exists as a set of such clusters. The proposed cyberspace implemented by WebVR and interactive 3D graphics can be considered as a dynamic learning environment that is convenient for discovering new significant articles, ideas and trends. It can be a powerful tool of information integration, because it allows you to visualize documents of different languages in a single space.