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Updated: Feb 11, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
Published on: November 24, 2021
Summarization of an online medical encyclopedia
Marcelo Fiszman1, Thomas C Rindflesch, Halil Kilicoglu
1National Library of Medicine, National Institutes of Health/DHHS, 8600 Rockville Pike MS43, Bethesda, MD 20894, USA.
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.
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