OAEI 2014::Large BioMed Track

Results OAEI 2014::Large BioMed Track

Results of the FMA-SNOMED matching problem

The following tables summarize the results for the tasks in the FMA-SNOMED matching problem.

AML provided the best results in terms of F-measure on both Task 3 and Task 4. AML also provided the best Recall and Precision in Task 3 and Task 4, respectively; while LogMapLite provided the best Precision in Task 3 and LogMap-Bio the best Recall in Task 4.

Overall, the results were less positive than in the FMA-NCI matching problem. As in the FMA-NCI matching problem, efficiency also decreases as the ontology size increases. The most important variations were suffered by LogMap-Lite and XMap in terms of precision. Furthermore, AOT, AOTL, RSDLWB could no complete neither Task 3 nor Task 4 in less than 10 hours. MaasMatch rose an "out of memory" exception in Task 4, while OMReasoner could not complete Task 4 within the permitted time.

Task 3: FMA-SNOMED small fragments

**Table 1:** Results for the largebio task 3.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	126	6,791	0.926	0.742	0.824	0	0.0%
LogMap-Bio	1,060	6,444	0.932	0.710	0.806	0	0.0%
LogMap	63	6,242	0.950	0.695	0.803	0	0.0%
XMap	35	7,443	0.858	0.737	0.793	13,429	56.9%
LogMap-C	119	4,536	0.958	0.508	0.664	0	0.0%
MaasMatch	4,605	8,117	0.655	0.674	0.664	21,946	92.9%
Average	839	5,342	0.870	0.554	0.644	4,578	19.4%
LogMapLite	13	1,645	0.968	0.208	0.343	773	3.3%
OMReasoner	691	1,520	0.713	0.156	0.256	478	2.0%

Task 4: FMA whole ontology with SNOMED large fragment

**Table 2:** Results for the largebio task 4.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	251	6,192	0.891	0.647	0.749	0	0.0%
LogMap	388	6,141	0.831	0.623	0.712	0	0.0%
LogMap-Bio	1,449	6,853	0.756	0.651	0.700	0	0.0%
Average	523	5,760	0.790	0.540	0.617	11,823	5.9%
LogMap-C	571	4,630	0.853	0.476	0.611	98	0.049%
XMap	390	8,926	0.558	0.633	0.593	66,448	33.0%
LogMapLite	90	1,823	0.852	0.208	0.335	4,393	2.2%