@conference {IT606,
	title = {IT606: Measuring the importance of annotation granularity to the detection of semantic similarity between phenotype profiles},
	booktitle = {International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016)},
	series = {Proceedings of the Joint International Conference on Biological Ontology and BioCreative (2016)},
	year = {2016},
	month = {11/30/16},
	publisher = {CEUR-ws.org Volume 1747},
	organization = {CEUR-ws.org Volume 1747},
	abstract = {<p>Inphenotypeannotationscuratedfromthebiolog-icalandmedicalliterature,considerablehumaneffortmustbeinvestedtoselectontologicalclassesthatcapturetheexpressivityoftheoriginalnaturallanguagedescriptions,andannotationgranularitycanalsoentailhighercomputationalcostsforpartic-ularreasoningtasks.Docoarseannotationsforcertainapplications?Here,wemeasurehowannotationgranularityaffectsthestatisticalbehaviorofsemanticsimilaritymetrics.Weusearandomizeddatasetofphenotypeprdrawnfrom57,051taxon-phenotypeannotationsinthePhenoscapeKnowledgebase.WecomparedqueryprhavingvariableproportionsofmatchingphenotypestosubjectdatabaseprusingbothpairwiseandgroupwiseJaccard(edge-based)andResnik(node-based)semanticsimilaritymetrics,andcomparedstatisticalperformanceforthreedifferentlevelsofannotationgranularity:entitiesalone,entitiesplusattributes,andentitiesplusqualities(withimplicitattributes).Allfourmetricsexaminedshowedmoreextremevaluesthanexpectedbychancewhenapproximatelyhalftheannotationsmatchedbetweenthequeryandsubjectprwithamoresuddendeclineforpairwisestatisticsandamoregradualoneforthegroupwisestatistics.Annotationgranularityhadanegligibleeffectonthepositionofthethresholdatwhichmatchescouldbediscriminatedfromnoise.Theseresultssuggestthatcoarseannotationsofphenotypes,atthelevelofentitieswithorwithoutattributes,maybetoidentifyphenotypeprwithstatisticallysemanticsimilarity.</p>
},
	url = {http://ceur-ws.org/Vol-1747/IT606_ICBO2016.pdf},
	author = {Prashanti Manda and James P. Balhoff and Todd J. Vision}
}
