July 2006 Volume 9 Number 3 - CiteSeerX

Matching Accuracy
70%
60%
50%
40%
30%
20%
10%
0%
t=0.6
t=0.7
t=0.8
t=0.9
t=1.0
t=0.6
t=0.7
t=0.8
t=0.9
t=1.0
t=0.6
t=0.7
t=0.8
Pair 1 Pair 2 Pair 3 Pair 4 Average
Figure 10. Improvement in matching accuracy of mapped ontologies
The average mapping result for all four pairs (Figure 9) shows that the threshold value 0.8 generates the best
precision and recall. It contributes towards improvement in the f-measure and matching accuracy in mapping
(Figure 10). Therefore, threshold value 0.8 will be adopted to automate the ontology mapping and merging
process. However, we desire to perform more experiments to justify the current threshold value for ontological
domains other than that of the academic domain.
OntoDNA and Ontology Mapping (An Integrated Approach) Comparison Evaluation Result
The statistics for Ehrig and Sure’s (2004) ontology mapping on measures at cut-off using a neural net similarity
strategy is extracted and compared with that of OntoDNA in terms of precision, recall and f-measure as shown in
Table 5 below. The statistics indicate the best results obtained in terms of precision among metric measures and
similarity strategies.
Table 5. Summarized of precision, recall and f-measure
t=0.9
t=1.0
OntoDNA Ontology Mapping (Ehrig & Sure, 2004)
Precision Recall F-Measure Precision Recall F-Measure
SWRC 0.9167 0.4630 0.6048 0.7500 0.6667 0.7059
Russia2 0.9752 0.5488 0.7024 0.7763 0.2822 0.4140
OntoDNA provides better precision compared to Ehrig and Sure’s ontology mapping tool (Figure 11). OntoDNA
shows significant improvement in terms of recall and f-measure for the Russia2 ontology. This is evidence that
OntoDNA can effectively address structural complexities and different ontological semantics. It is also noted
that precision and recall relationships are inverse; increase in precision tends to result in decrease in recall, and
vice-verse (Soboroff, 2005). There is tradeoff between precision and recall. Hence, it is up to the designer to
decide on a suitable level of tradeoff.
precision, recall & f-measure
1.2000
1.0000
0.8000
0.6000
0.4000
0.2000
0.0000
OntoDNA vs. Ontology Mapping (Ehrig & Sure, 2004)
t=0.6
t=0.7
t=0.8
t=0.9
t=1.0
t=0.6
OntoDNA Ontology Mapping (Ehrig & Sure, 2004)
SWRC Russia2 SWRC Russia 2 SWRC Russia2
precision recall f-measure
Figure 11. Comparison result between OntoDNA with Ehrig and Sure’s ontology mapping
t=0.7
t=0.8
t=0.9
t=1.0
39