@article{
 id = {be213591-3582-3cc2-b946-149ddd0f888c},
 title = {Summarization of an online medical encyclopedia.},
 type = {article},
 year = {2004},
 identifiers = {[object Object]},
 keywords = {Disease,Encyclopedias as Topic,Humans,MedlinePlus,Natural Language Processing,Online Systems,Semantics,Unified Medical Language System},
 created = {2013-10-09T05:48:36.000Z},
 pages = {506-10},
 volume = {107},
 websites = {http://www.ncbi.nlm.nih.gov/pubmed/15360864},
 month = {1},
 accessed = {2013-10-03},
 file_attached = {true},
 profile_id = {f6533b76-ddf1-3a1d-8998-aa060f033d83},
 group_id = {19368b1d-d446-3e1d-846b-7b3b554cc058},
 last_modified = {2013-10-09T05:51:28.000Z},
 tags = {summarization},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Fiszman2004},
 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.},
 bibtype = {article},
 author = {Fiszman, Marcelo and Rindflesch, Thomas C and Kilicoglu, Halil},
 journal = {Studies in health technology and informatics},
 number = {Pt 1}
}

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