Towards an intelligent framework to understand and feed the web

Abstract

The Web is becoming a mirror of the "real" physical world. More and more aspects of our life move to the Web, thus also transforming this world. And the diversity of ways to communicate over the Internet has enormously grown. In this context communicating the right thing at the right time in the right way to the right person has become a remarkable challenge. In this conceptual paper we propose a framework to apply semantic technologies in combination with statistical and learning methods on Web and social media data to build a decision support framework. This framework should help professionals as well as normal users to optimize the spread of their information and the potential impact of this information on the Web. © 2012 Springer-Verlag.