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Table 12 Experimental confirmation of the \(k{\bar{E}}^2_{C}\) factor impacting the linear scalability of AncSPL for non-tree-like ontologies (\(TC_3\)) shown in Fig. 3

From: HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey

Ontology

\({\bar{E}}_{C}\)

\(\widehat{k{\bar{E}}^2_{C}}\)

\(({\mu }s)\)

\({\bar{E}}^2_{C}/{\bar{E}}^2_{WN}\)

\(\widehat{{\bar{E}}^2_{C}/{\bar{E}}^2_{WN}}\)

SNOMED-CT

72.02

1.191

7.79

5.39

GO

31.14

0.3277

1.46

1.48

WordNet (WN)

25.80

0.2210

1

1

  1. First column shows the average number of adjacent nodes per ancestor set for each node in ontology C, denoted by \({\bar{E}}_{C}\). Second column shows the estimated value for the factor \(k{\bar{E}}^2_{C}\) in \(TC_3\) obtained by fitting the scalability plot shown in Fig. 3 to the line \(t_{{\mu }s} = \alpha + (k{\bar{E}}^2_{C})N\). Then, third and fourth columns compare the theoretical and experimental expected ratios between the time complexity (slope) of two different ontologies using WordNet (WN) as baseline
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BMC Bioinformatics

ISSN: 1471-2105

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