New directions in biomedical text annotation: definitions, guidelines and corpus construction

Background: While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined. Results: We have identified five qualitative dimensions that we believe characterize a broad range of scientific sentences, and are therefore useful for supporting a general approach to text-mining: focus, polarity, certainty, evidence, and directionality. We def...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: W. John Wilbur, Andrey Rzhetsky, Hagit Shatkay
• Keywords: Annotations, Biomedical Text, Biomedical Text Mining, BMCBI 2006