A Maximum-Entropy approach for accurate document annotation in the biomedical domain

• Published in: Journal of biomedical semantics Vol. 3; no. Suppl 1; p. S2
• Main Authors: Tsatsaronis, George, Macari, Natalia, Torge, Sunna, Dietze, Heiko, Schroeder, Michael
• Format: Journal Article
• Language: English
• Published: England BioMed Central 24.04.2012; BioMed Central Ltd
• Subjects: Algorithms; Ambiguity; Annotations; Automation; BASIC BIOLOGICAL SCIENCES; Bayesian analysis; Classification; Decision trees; Domains; Entropy; Information processing; Maximum entropy; Medical Subject Headings-MeSH; Ontology; Proceedings; Recall; Robustness; Search engines; Semantics; Subject heading schemes; Thesauri

The increasing number of scientific literature on the Web and the absence of efficient tools used for classifying and searching the documents are the two most important factors that influence the speed of the search and the quality of the results. Previous studies have shown that the usage of ontolo...