2012
DOI: 10.1007/978-3-642-31374-5_36
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Reimplementing the Mathematics Subject Classification (MSC) as a Linked Open Dataset

Abstract: Abstract. The Mathematics Subject Classification (MSC) is a widely used scheme for classifying documents in mathematics by subject. Its traditional, idiosyncratic conceptualization and representation makes the scheme hard to maintain and requires custom implementations of search, query and annotation support. This limits uptake e.g. in semantic web technologies in general and the creation and exploration of connections between mathematics and related domains (e.g. science) in particular. This paper presents th… Show more

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Cited by 7 publications
(3 citation statements)
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“…Firstly, domain ontology needs refinement and unification, because it has been developed by different people: some domains are more detailed, the last increases the density of term links and influences term weight. To improve the quality of term significance calculation domain ontology has to be integrated with external resources, i.e., Mathematics Subject Classification (MSC) [13]. Secondly, broad experiments with learners are critical for quality improvement: new metrics can be added and learning strategies can be revealed bases on the analysis of users statistics.…”
Section: Resultsmentioning
confidence: 99%
“…Firstly, domain ontology needs refinement and unification, because it has been developed by different people: some domains are more detailed, the last increases the density of term links and influences term weight. To improve the quality of term significance calculation domain ontology has to be integrated with external resources, i.e., Mathematics Subject Classification (MSC) [13]. Secondly, broad experiments with learners are critical for quality improvement: new metrics can be added and learning strategies can be revealed bases on the analysis of users statistics.…”
Section: Resultsmentioning
confidence: 99%
“…The first conversion of the MSC to RDF Linked Data was published in 2012 as a Turtle serialisation [7,8]. The motivation was to encourage reuse, maintenance, and versatile access with a low-threshold according to the best practices of the time [8]. The modeling decisions made then have been comprehensively documented in [7].…”
Section: Msc 2010 Skos Modelmentioning
confidence: 99%
“…The data required to represent the complete model for MSC 2010 are publicly available 8 . This approach inspired other projects tackling semantification of mathematics according to LOD principles, for example OntoMathPRO [10] or coli-conc [1].…”
Section: Msc 2010 Skos Modelmentioning
confidence: 99%