July 2006 Volume 9 Number 3 - CiteSeerX

Precision: measures the number of correct mapping found against the total number of retrieved mappings.
number of correct found mapping
precision = Eq. 1
number of retrieved mappings
Recall: measures the number of correct mapping found comparable to the total number of existing mappings.
number of correct found mapping
recall = Eq. 2
number of existing mappings
F-measure: combines measure of precision and recall as single efficiency measure.
2 x precision x recall
f - measure = Eq. 3
precision + recall
Results and Discussion
The result of each semantic similarity approach is presented in Table 4. In terms of recall and precision,
Levenshtein edit distance measure yields better results against the Leacock-Chodorow similarity measure and the
combined WordNet-string matching approach in discovering correlation between two candidate mappings.
String matching using Levenshtein edit distance generates an accuracy rate of 93.33% comparable to the human
experts’ assessment as shown in Figure 7.
Table 4. Comparison of lexical measures for 4 paired ontologies based on thresholds 0.6 to 0.1
String Matching Measure (SM) WordNet Matching Measure (WN) Combined Measure (SM + WN)
Pair 1 Pair 1 Pair 1
Threshold 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 t=0.9 t=1.0
Precision 0.6667 0.8000 1.0000 1.0000 1.0000 0.3333 0.5714 0.6667 1.0000 1.0000 0.5000 0.5714 0.5714 1.0000 1.0000
Recall 0.4444 0.4444 0.2222 0.5556 0.2222 0.2222 0.4444 0.4444 0.2222 0.4444 0.4444 0.4444 0.4444 0.2222 0.2222
F-Measure 0.5333 0.5714 0.3636 0.7143 0.3636 0.2667 0.5000 0.5333 0.3636 0.6154 0.4706 0.5000 0.5000 0.3636 0.3636
Pair 2 Pair 2 Pair 2
Threshold 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 t=0.9 t=1.0
Precision 0.7500 0.6667 0.7500 0.7500 0.7500 0.7500 0.8000 0.7500 0.6667 0.8000 0.8000 0.8000 0.6000 0.7500 0.6667
Recall 0.5000 0.3333 0.5000 0.5000 0.5000 0.5000 0.6667 0.5000 0.3333 0.6667 0.6667 0.6667 0.5000 0.5000 0.3333
F-Measure 0.6000 0.4444 0.6000 0.6000 0.6000 0.6000 0.7273 0.6000 0.4444 0.7273 0.7273 0.7273 0.5455 0.6000 0.4444
Pair 3 Pair 3 Pair 3
Threshold 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 t=0.9 t=1.0
Precision 0.5000 1.0000 1.0000 1.0000 1.0000 0.2857 0.3333 0.2857 1.0000 1.0000 0.2857 0.1667 0.2857 1.0000 1.0000
Recall 0.6667 0.6667 0.3333 0.3333 0.3333 0.6667 0.6667 0.6667 0.3333 0.3333 0.6667 0.3333 0.6667 0.3333 0.6667
F-Measure 0.5714 0.8000 0.5000 0.5000 0.5000 0.4000 0.4444 0.4000 0.5000 0.5000 0.4000 0.2222 0.4000 0.5000 0.8000
Pair 4 Pair 4 Pair 4
Threshold 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 t=0.9 t=1.0
Precision 1.0000 1.0000 0.9831 0.9752 0.9762 0.7778 0.7500 0.6667 0.9091 1.0000 1.0000 0.9231 1.0000 0.9524 0.9643
Recall 0.1767 0.1814 0.5395 0.5488 0.5721 0.0326 0.0279 0.0186 0.0465 0.0465 0.0465 0.0558 0.0372 0.1860 0.2512
F-Measure 0.3004 0.3071 0.6967 0.7024 0.7214 0.0625 0.0538 0.0362 0.0885 0.0889 0.0889 0.1053 0.0717 0.3113 0.3985
Average Average Average
Threshold 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 t=0.9 t=1.0
Precision 0.7292 0.8667 0.9333 0.9313 0.9315 0.5367 0.6137 0.5923 0.8939 0.9500 0.6464 0.6153 0.6143 0.9256 0.9077
Recall 0.4470 0.4065 0.3988 0.4844 0.4069 0.3554 0.4514 0.4074 0.2339 0.3727 0.4561 0.3751 0.4121 0.3104 0.3683
F-Measure 0.5013 0.5307 0.5401 0.6292 0.5463 0.3323 0.4314 0.3924 0.3491 0.4829 0.4217 0.3887 0.3793 0.4437 0.5017
1.0000
0.8000
0.6000
0.4000
0.2000
0.0000
t=0.6
t=0.7
t=0.8
t=0.9
t=1.0
Precision Recall F-Measure
t=0.6
t=0.7
t=0.8
String Matching Measure WordNet Matching Measure Combined Measure
t=0.9
t=1.0
t=0.6
Figure 7. Average values of lexical measures
t=0.7
t=0.8
t=0.9
t=1.0
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