OAEI 2015::Large BioMed Track

Results OAEI 2015::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.

XMAP-BK and AML provided the best results in terms of F-measure in Task 1 and Task 2. Note that, the use of background knowledge based on the UML-Metathesaurus has an important impact in the performance of XMAP-BK. LogMapBio 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, ServOMBI, CroMacther, LiLy, DKP-AOM-Lite and DKP-AOM could not complete Task 2.

* Uses background knowledge based on the UMLS-Metathesaurus as the LargeBio reference alignments.

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
XMAP-BK *	31	2,714	0.971	0.902	0.935	2,319	22.6%
AML	36	2,690	0.960	0.899	0.928	2	0.019%
LogMap	25	2,747	0.949	0.901	0.924	2	0.019%
LogMapBio	1,053	2,866	0.926	0.917	0.921	2	0.019%
LogMapLite	16	2,483	0.967	0.819	0.887	2,045	19.9%
ServOMBI	234	2,420	0.970	0.806	0.881	3,216	31.3%
XMAP	26	2,376	0.970	0.784	0.867	2,219	21.6%
LogMapC	106	2,110	0.963	0.710	0.817	2	0.019%
Average	584	2,516	0.854	0.733	0.777	2,497	24.3%
Lily	740	3,374	0.602	0.720	0.656	9,279	90.2%
DKP-AOM-Lite	1,579	2,665	0.640	0.603	0.621	2,139	20.8%
DKP-AOM	1,491	2,501	0.653	0.575	0.611	1,921	18.7%
CroMatcher	2,248	2,806	0.570	0.570	0.570	9,301	90.3%
RSDLWB	17	961	0.964	0.321	0.482	25	0.2%

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
XMAP-BK *	337	2,802	0.872	0.849	0.860	1,222	0.8%
AML	262	2,931	0.832	0.856	0.844	10	0.007%
LogMap	265	2,693	0.854	0.802	0.827	9	0.006%
LogMapBio	1,581	3,127	0.773	0.848	0.809	9	0.006%
XMAP	302	2,478	0.866	0.743	0.800	1,124	0.8%
Average	467	2,588	0.818	0.735	0.759	3,742	2.6%
LogMapC	569	2,108	0.879	0.653	0.750	9	0.006%
LogMapLite	213	3,477	0.673	0.820	0.739	26,478	18.1%
RSDLWB	211	1,094	0.798	0.307	0.443	1,082	0.7%