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Lexical Systems & Tools

Project information
Researchers: 

LHNCBC's Lexical Systems Group develops and maintains the SPECIALIST lexicon and the tools that support and exploit it. The SPECIALIST Lexicon and NLP Tools are at the center of NLM's natural language research, providing a foundation for all our natural language processing efforts. In general, we investigate the contributions that natural language processing techniques can make to the task of mediating between the language of users and the language of online biomedical information resources. The SPECIALIST NLP Tools facilitate natural language processing by helping application developers with lexical variation and text analysis tasks in the biomedical domain.

Recently, the Lexical Systems Group began a project to enhance the derivational-variants function of the lexical tools. The derivational-variants function uses a set of derivational facts and rules to generate or identify derivational variants of input terms. Derivational variants are words related by a word-formation process like suffixation, prefixation or conversion (change of category). The current derivational variant system has only suffix rules and facts. These rules and facts are hand entered and curated. In order to add suffixation and conversion functionality to the system, the PDM team has developed a method to automatically extract candidate pairs of words that may be derivationally related, which helps automate the creation of rules and facts for suffixation and conversion.

The SPECIALIST Lexicon and Lexical tools are open source and freely downloadable. The 2012 release of the SPECIALIST Lexicon will contain over 462,000 records, representing over 830,000 forms, an increase of over 13,000 records from the 2011 release. Many of the new terms are derived from de-identified clinical records from our own De-identification project and from the MIMIC database.

Publications/Tools: 
Lu C, Tormey D, McCreedy L, Browne AC. • A Systematic Approach for Automatically Generating Derivational Variants in Lexical Tools Based on the SPECIALIST Lexicon. IEEE IT Professional Magazine, May/June, 2012, p. 36-42.
Lu C, Browne AC. Converting Unicode Lexicon and Lexical Tools for ASII NLP Applications AMIA Annu Symp Proc 2011:1870.
Lu C, Divita G, Browne AC. Development of Visual Tagging Tool AMIA Annu Symp Proc 2010:1156.
Kilicoglu H, Fiszman M, Rosemblat G, Marimpietri S, Rindflesch TC. Arguments of Nominals in Semantic Interpretation of Biomedical Text BioNLM Workshop Proc, Assoc. for Computational Linguistics 2010
Lu C, Browne AC, Allen C, Divita G. Using Lexical tools to convert Unicode characters to ASCII AMIA Annu Symp Proc. 2008 Nov 6:1031.
Bangalore AK, Divita G, Humphrey SM, Browne AC, Thorn KE. Automatic Categorization of Google Search Results for Medical Queries using JDI Medinfo 2007: Proc. of the 11th World Congress on Health (Medical) Informatics
Bashyam V, Divita G, Bennett DB, Browne AC, Taira RK. A normalized lexical lookup approach to identifying UMLS concepts in free text. Stud Health Technol Inform. 2007;129(Pt 1):545-9.
Tolentino HD, Matters MD, Walop W, Law B, Tong W, Liu F, Fontelo P, Kohl K, Payne DC. A UMLS-based Spell Checker for Natural Language Processing in Vaccine Safety. BMC Med Inform Decis Mak. 2007 Feb 12;7:3. DOI: 10.1186/1472-6947-7-3.
Keselman A, Massengale L, Ngo L, Browne A, Zeng Q. The Effect of User Factors on Consumer Familiarity with Health Terms: Using Gender as a Proxy for Background Knowledge about Gender-Specific Illnesses ISBMDA 2006: 472-481
Divita G, Browne AC, Loanne R. dTagger: A POS Tagger AMIA Annu Symp Proc. 2006:200-3

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