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Semantic Knowledge Representation

Diagram of semantic relationships
Project information
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Note: this web page will be archived on or around October 1 2019 and will be part of the NLM Lister Hill National Center for Biomedical Communications archive collection.

Semantic Knowledge Representation

In support of innovative information management applications in biomedicine as well as basic research, the Semantic Knowledge Representation project (SKR) efforts use symbolic natural language processing based on the UMLS knowledge sources. SKR research examples include developing and applying the literature-based discovery paradigm using semantic predications. One such project looked into the physiology of sleep and associated pathologies, such as declining sleep quality in aging men, restless legs syndrome, and obstructive sleep apnea; another project exploited predications and graph theory for automatic summarization of biomedical text.


A core SKR resource is the SemRep program, which extracts semantic predications from text. Originally developed for biomedical research, SemRep was subsequently extended to genetic etiology and pharmacogenomics. Then, through a general methodology based on ontology and thesauri development, SemRep's application was extended to other fields, such as influenza epidemic preparedness and health promotion.  By applying natural language processing techniques, our research can better inform patients, health care providers, researchers, and the general public.


The SKR project maintains SemMedDB, a repository of 96.3 million SemRep predications (subject-predicate-object triples) extracted our semantic interpreter SemRep from all MEDLINE citations up to Dec. 2018. This database supports the Semantic MEDLINE web application (SemMed), which integrates PubMed searching, SemRep predications, automatic summarization, and data visualization. The application is intended to help users manage the results of PubMed searches. Output is visualized as an informative graph with links to the original MEDLINE citations.

Downloads related to SemRep, SemMedDB, and SKR are available from our Access to SemRep/SemMedDB/SKR Resources page.

Zhang R, Cairelli MJ, Fiszman M, Rosemblat G, Kilicoglu H, Rindflesch TC, Pakhomov SV, Melton GB. Using semantic predications to uncover drug-drug interactions in clinical data. J Biomed Inform. 2014 Jun;49:134-47. doi: 10.1016/j.jbi.2014.01.004. Epub 2014 Jan 19.
Kastrin A, Rindflesch TC, Hristovski D. Link prediction on the Semantic MEDLINE Network. Proceedings of the 17th International conference on Discovery Science.
Cohen T, Widdows D, Rindflesch TC. Expansion-by-analogy: A vector symbolic approach to semantic search. AAAI-Fall 2014 Symposium on Quantum Informatics for Cognitive, Social, and Semantic Processes.
Kastrin A, Rindflesch TC, Hristovski D. Link prediction in a MeSH co-occurrence network: preliminary results. Stud Health Technol Inform. 2014;205:579-83.
Rosemblat G, Shin D, Kilicoglu H, Sneiderman C, Rindflesch TC. A methodology for extending domain coverage in SemRep. J Biomed Inform. 2013 Dec;46(6):1099-107. doi: 10.1016/j.jbi.2013.08.005. Epub 2013 Aug 21.
Cairelli MJ, Miller CM, Fiszman M, Workman TE, Rindflesch TC. Semantic MEDLINE for discovery browsing: using semantic predications and the literature-based discovery paradigm to elucidate a mechanism for the obesity paradox. AMIA Annu Symp Proc. 2013 Nov 16;2013:164-73. eCollection 2013.
Workman TE, Rosemblat G, Fiszman M, Rindflesch TC. A literature-based assessment of concept pairs as a measure of semantic relatedness. AMIA Annu Symp Proc. 2013 Nov 16;2013:1512-21. eCollection 2013.
Mishra R, Del Fiol G, Kilicoglu H, Jonnalagadda S, Fiszman M. Automatically extracting clinically useful sentences from UpToDate to support clinicians' information needs. AMIA Annu Symp Proc. 2013 Nov 16;2013:987-92. eCollection 2013.
Friedman C, Rindflesch TC, Corn M. Natural language processing: state of the art and prospects for significant progress, a workshop sponsored by the National Library of Medicine. J Biomed Inform. 2013 Oct;46(5):765-73. doi: 10.1016/j.jbi.2013.06.004. Epub 2013 Jun 25.
Jonnalagadda SR, Del Fiol G, Medlin R, Weir C, Fiszman M, Mostafa J, Liu H. Automatically extracting sentences from Medline citations to support clinicians' information needs. J Am Med Inform Assoc. 2013 Sep-Oct;20(5):995-1000. doi: 10.1136/amiajnl-2012-001347. Epub 2012 Oct 25.