title: Summarization of an online medical encyclopedia.
abstract: We explore a knowledge-rich (abstraction) approach to summarization and apply it to multiple documents from an online medical encyclopedia. A semantic processor functions as the source interpreter and produces a list of predications. A transformation stage then generalizes and condenses this list, ultimately generating a conceptual condensate for a given disorder topic. We provide a preliminary evaluation of the quality of the condensates produced for a sample of four disorders. The overall precision of the disorder conceptual condensates was 87%, and the compression ratio from the base list of predications to the final condensate was 98%. The conceptual condensate could be used as input to a text generator to produce a natural language summary for a given disorder topic.
authors.affiliation: National Library of Medicine, National Institutes of Health/DHHS, 8600 Rockville Pike MS43, Bethesda, MD 20894, USA.
authors.forename: Marcelo
authors.initials: M
authors.lastname: Fiszman
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Rindflesch
authors.forename: Halil
authors.initials: H
authors.lastname: Kilicoglu
mesh_terms: D004194:Disease; D004690:Encyclopedias as Topic; D006801:Humans; D049293:MedlinePlus; D009323:Natural Language Processing; D009862:Online Systems; D012660:Semantics; D017432:Unified Medical Language System