Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9871
Title: Ontology of core data mining entities
Authors: Panov, P
Soldatova, L
Dzeroski, S
Keywords: Science & Technology;Technology;Computer Science, Artificial Intelligence;Computer Science, Information Systems;Computer Science;Ontology of data mining;Mining structured data;Domain ontology;COORDINATED EVOLUTION;KNOWLEDGE DISCOVERY;BIOLOGICAL-ACTIVITY;REGRESSION TREES;CLASSIFICATION;ARTEMISININ;ENVIRONMENT;ENSEMBLES;PREDICT;MODELS
Issue Date: 2014
Publisher: SPRINGER
Citation: DATA MINING AND KNOWLEDGE DISCOVERY, 28:5-6, pp. 1222 - 1265, 2014
Abstract: In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend.
URI: http://link.springer.com/article/10.1007%2Fs10618-014-0363-0
http://bura.brunel.ac.uk/handle/2438/9871
DOI: http://dx.doi.org/10.1007/s10618-014-0363-0
ISSN: 1384-5810
Appears in Collections:Dept of Computer Science Research Papers

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