Search

To realize the vision of a Semantic Web for Life Sciences, discovering relations between resources is essential. It is very difficult to automatically extract relations from Web pages expressed in natural language formats. On the other hand, because of the explosive growth of information, it is difficult to manually extract the relations. In this paper we present techniques to automatically discover relations between biomedical resources from the Web. For this purpose we retrieve relevant information from Web Search engines and Pubmed database using various lexico-syntactic patterns as queries over SOAP web services. The patterns are initially handcrafted but can be progressively learnt. The extracted relations can be used to construct and augment ontologies and knowledge bases. Experiments are presented for general biomedical relation discovery and domain specific search to show the usefulness of our technique.

Most of the existing IT applications are designed to cater to a small fraction of the human population. The precluded set consists of more than a billion people who either cannot afford a PC and Internet or are not skilled enough to be able to use them. However, the IT needs of this segment is similar in nature and perhaps more crucial than that of the current user segment. Designing systems for these underprivileged people poses several technological challenges: Due to low literacy levels the user interface has to be radically simplified, and the user devices have to be affordable. These and other requirements motivate a shift of complexity and computation from end-user devices to the network, tremendously increasing the expectations from the infrastructure. In this paper, we present an overview of technology developed and solutions built under Pyr.mea.IT project towards enabling IT for the masses.

Information Visualization can make hypermedia systems more usable by presenting a site map to assist in navigation. In this paper we explain some of the difficulties in developing effective visualizations of hypermedia information spaces and highlight some of the key systems and techniques that have been developed to overcome the difficulties. Finally, we discuss some of the major challenges for the next generation of information visualization researchers.