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2014 | OriginalPaper | Buchkapitel

Big Complex Biomedical Data: Towards a Taxonomy of Data

verfasst von : Andreas Holzinger, Christof Stocker, Matthias Dehmer

Erschienen in: E-Business and Telecommunications

Verlag: Springer Berlin Heidelberg

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Abstract

Professionals in the Life Sciences are faced with increasing masses of complex data sets. Very few data is structured, where traditional information retrieval methods work perfectly. A large portion of data is weakly structured; however, the majority falls into the category of unstructured data. To discover previously unknown knowledge from this data, we need advanced and novel methods to deal with the data from two aspects: time (e.g. information entropy) and space (e.g. computational topology). In this paper we show some examples of biomedical data and discuss a taxonomy of data with the specifics on medical data sets.

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Metadaten
Titel
Big Complex Biomedical Data: Towards a Taxonomy of Data
verfasst von
Andreas Holzinger
Christof Stocker
Matthias Dehmer
Copyright-Jahr
2014
Verlag
Springer Berlin Heidelberg
Buch
E-Business and Telecommunications

Print ISBN: 978-3-662-44790-1

Electronic ISBN: 978-3-662-44791-8

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-662-44791-8_1

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