A novel semantic web browser for user centric information retrieval: PERSON
As semantic web technologies mature and consequently more semantic web data is published on the web, there is a growing need for tools to access and use this data in user friendly ways. The most generic tool to access semantic web data is the common web browser. Developing plug-ins for advanced web browsers is one way of adding semantic information to web documents automatically or semi-automatically. To enable this enhancement, we present a novel semantic web browser called PERSON which is short for PERsonal Semantic extensiON. PERSON is an extension for Mozilla Firefox Web Browser and it adds semantics to users browsing experience by annotating web resources, associating them in categorical, entity-based manner and presenting more meaningful, structured documents to users. As a notable difference, semantic layer provided by PERSON works not only on web pages navigated by users but also on RSS data of user choice. Additionally, acquired content from web resources associated with linked data domains bring users together with structured information easily. In this paper, we evaluate PERSON as a new approach for semantic web browsing and present the analysis, design and implementation of PERSON and compare its features with related tools.
semantic web browsing linked data semantic annotation information extraction named entity recognition