@inbook{67b7afd12bc34eb2a405ae55236bb64c,
title = "Linking Biomedical Data to the Cloud",
abstract = "The application of Knowledge Discovery and Data Mining approaches forms the basis of realizing the vision of Smart Hospitals. For instance, the automated creation of high-quality knowledge bases from clinical reports is important to facilitate decision making processes for clinical doctors. A subtask of creating such structured knowledge is entity disambiguation that establishes links by identifying the correct semantic meaning from a set of candidate meanings to a text fragment. This paper provides a short, concise overview of entity disambiguation in the biomedical domain, with a focus on annotated corpora (e.g. CalbC), term disambiguation algorithms (e.g. abbreviation disambiguation) as well as gene and protein disambiguation algorithms (e.g. inter-species gene name disambiguation). Finally, we provide some open problems and future challenges that we expect future research will take into account.",
keywords = "Linked data cloud, Entity disambiguation, Text annotation, Natural language processing, Knowledge bases, n/a OA procedure",
author = "Stefan Zwicklbauer and Christin Seifert and Michael Granitzer",
year = "2015",
doi = "10.1007/978-3-319-16226-3_9",
language = "English",
isbn = "978-3-319-16225-6",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "209--235",
editor = "Andreas Holzinger and Carsten R{\"o}cker and Martina Ziefle",
booktitle = "Smart Health",
address = "Germany",
}