OAEI 2014::Large BioMed Track

Results OAEI 2014::Large BioMed Track

Results of the FMA-NCI matching problem

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

LogMap-Bio and AML provided the best results in terms of both Recall and F-measure in Task 1 and Task 2, respectively. OMReasoner provided the best results in terms of precision, although its recall was below average. From the last year participants, XMap and MaasMatch improved considerably their performance with respect to both runtime and F-measure. AML and LogMap obtained again very good results. LogMap-Bio improves LogMap's recall in both tasks, however precision is damaged specially in Task 2.

Note that efficiency in Task 2 has decreased with respect to Task 1. This is mostly due to the fact that larger ontologies also involves more possible candidate alignments and it is harder to keep high precision values without damaging recall, and vice versa. Furthermore, AOT, AOTL, RSDLWB and MaasMatch could no complete Task 2. The first three did not finish in less than 10 hours while MaasMatch rose an "out of memory" exception.

Task 1: FMA-NCI small fragments

**Table 1:** Results for the largebio task 1.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	27	2,690	0.960	0.899	0.928	2	0.02%
LogMap	14	2,738	0.946	0.897	0.921	2	0.02%
LogMap-Bio	975	2,892	0.914	0.918	0.916	467	4.5%
XMap	17	2,657	0.932	0.848	0.888	3,905	38.0%
LogMapLite	5	2,479	0.967	0.819	0.887	2,103	20.5%
LogMap-C	81	2,153	0.962	0.724	0.826	2	0.02%
MaasMatch	1,460	2,981	0.808	0.840	0.824	8,767	85.3%
Average	3,193	2,287	0.910	0.704	0.757	2,277	22.2%
AOT	9,341	3,696	0.662	0.855	0.746	8,373	81.4%
OMReasoner	82	1,362	0.995	0.466	0.635	56	0.5%
RSDLWB	2,216	728	0.962	0.236	0.380	22	0.2%
AOTL	20,908	790	0.902	0.237	0.375	1,356	13.2%

Task 2: FMA-NCI whole ontologies

**Table 2:** Results for the largebio task 2.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	112	2,931	0.832	0.856	0.844	10	0.007%
LogMap	106	2,678	0.863	0.808	0.834	13	0.009%
LogMap-Bio	1,226	3,412	0.724	0.874	0.792	40	0.027%
XMap	144	2,571	0.835	0.745	0.787	9,218	6.3%
Average	5,470	2,655	0.824	0.746	0.768	5,122	3.5%
LogMap-C	289	2,124	0.877	0.650	0.747	9	0.006%
LogMapLite	44	3,467	0.675	0.819	0.740	26,441	18.1%
OMReasoner	36,369	1,403	0.964	0.466	0.628	123	0.084%