Semantic management of scholarly literature: A wiki-based approach

Abstract

The abundance of available literature in online repositories poses more challenges rather than expediting the task of retrieving content pertaining to a knowledge worker's information need. The rapid growth of the number of scientific publications has encouraged researchers from various domains to look for automatic approaches that can extract knowledge from the vast amount of available literature. Recently, a number of desktop and web-based applications have been developed to aid researchers in retrieving documents or enhancing them with semantic annotations [1,2]; yet, an integrated, collaborative environment that can encompass various activities of a researcher from assessing the writing quality of a paper to finding complementary work of a subject is not readily available. The hypothesis behind the proposed research work is that knowledge-intensive literature analysis tasks can be improved with semantic technologies. In this paper, we present the Zeeva system, as an empirical evaluation platform with integrated intelligent assistants that collaboratively work with humans on textual documents and use various techniques from the Natural Language Processing (NLP) and Semantic Web domains to manage and analyze scholarly publications. © 2014 Springer International Publishing.