LINNAEUS: A species name identification system for biomedical literature

Background: The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles. Results: In this paper we describe an open-source species name recognition and normalization software system, LINNAEUS, and evaluate its performance relative to several automatically generated biomedical corpora, as well as a novel corpus of full-text documents manually annotated for species mentions. LINNAEUS uses a dictionary-based approach (implemented as an efficient deterministic finite-state automaton) to identify species names and a set of heuristics to resolve ambiguous mentions. When compared against our manually annotated corpus, LINNAEUS performs with 94% recall and 97% precision at the mention level, and 98% recall and 90% precision at the document level. Our system successful...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Martin Gerner, Goran Nenadic, Casey M. Bergman
• Keywords: Biomedical, Biomedical Literature, BMCBI 2010, Species Names