OAEI 2015::Large BioMed Track

Results OAEI 2015::Large BioMed Track

Results of the SNOMED-NCI matching problem

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

AML provided the best results in terms of both Recall and F-measure in Task 5 and 6, while RSDLWB and XMAP provided the best results in terms of precision in Task 5 and 6, respectively.

Unlike in the FMA-NCI and FMA-SNOMED mathcing problems, the use of the UML-Metathesaurus did not have an impact in the performance of XMAP-BK, which obtained almost identical results as XMAP.

As in the previous matching problems, efficiency decreases as the ontology size increases. Furthermore, LiLy, DKP-AOM-Lite, DKP-AOM, ServOMBI and CroMatcher could not complete neither Task 5 nor Task 6 in less than 12 hours.

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

Task 5: SNOMED-NCI small fragments

**Table 1:** Results for the largebio task 5.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	470	14,141	0.917	0.724	0.809	≥0	≥0.000%
LogMapBio	3,298	12,855	0.940	0.674	0.785	≥0	≥0.000%
LogMap	410	12,384	0.958	0.663	0.783	≥0	≥0.000%
XMAP-BK *	396	11,674	0.928	0.606	0.733	≥1	≥0.001%
XMAP	394	11,674	0.928	0.606	0.733	≥1	≥0.001%
LogMapLite	212	10,942	0.949	0.567	0.710	≥60,450	≥80.4%
Average	1,055	11,092	0.938	0.577	0.703	12,262	16.3%
LogMapC	3,039	9,975	0.914	0.510	0.655	≥0	≥0.000%
RSDLWB	221	5,096	0.967	0.267	0.418	≥37,647	≥50.0%

Task 6: NCI whole ontology with SNOMED large fragment

**Table 2:** Results for the largebio task 6.
System	Time (s)	# Mappings	Scores			Incoherence Analysis
System	Time (s)	# Mappings	Precision	Recall	F-measure	Unsat.	Degree
AML	584	12,821	0.904	0.650	0.756	≥2	≥0.001%
LogMapBio	3,327	12,745	0.853	0.609	0.711	≥4	≥0.002%
LogMap	1,062	12,222	0.870	0.596	0.708	≥4	≥0.002%
XMAP-BK *	925	10,454	0.913	0.536	0.675	≥0	≥0.000%
XMAP	905	10,454	0.913	0.535	0.675	≥0	≥0.000%
LogMapLite	427	12,894	0.797	0.567	0.663	≥150,656	≥79.5%
Average	1,402	10,764	0.878	0.526	0.649	29,971	15.8%
LogMapC	3,553	9,100	0.882	0.450	0.596	≥2	≥0.001%
RSDLWB	436	5,427	0.894	0.265	0.408	≥89,106	≥47.0%