Knowledge extraction for literature review

Abstract

Researchers in all domains need to keep abreast with recent scientific advances. Finding relevant publications and reviewing them is a labor-intensive task that lacks efficient automatic tools to support it. Current tools are limited to standard keyword-based search systems that return potentially relevant documents and then leave the user with a monumental task of sifting through them. In this paper, we present a semantic-driven system to automatically extract the most important knowledge from a publication and reduces the effort required for the literature review. The system extracts key findings from biomedical papers in PubMed, populates a predefined template and displays it. This allows the user to get the key ideas of the content even before opening or downloading the publication.