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Generating Domain Terminologies using Root- and Rule-Based Terms
Published
Author(s)
Talapady N. Bhat, John T. Elliott, Ursula R. Kattner, Carelyn E. Campbell, Eswaran Subrahmanian, Ram D. Sriram, Jacob Collard, Monarch Ira
Abstract
Motivated by the need for exible, intuitive, reusable, and normalized ter- minology for the semantic web, we present a general approach for generat- ing sets of such terminologies from nat- ural language documents. The terms that this approach generates are root- and rule-based terms, generated by a series of rules designed to be exible, to evolve, and, perhaps most impor- tant, to protect against ambiguity and reduce semantically similar but syn- tactically distinct phrases to a normal form. This approach combines several linguistic and computational methods that can be automated with the help of training sets to quickly and consis- tently extract normalized terms. We discuss how this can be extended as natural language technologies improve and how the strategy applies to com- mon use-cases such as search, docu- ment entry and archiving, and cura- tion
Root and rule-based terminology, Material Genome Initiative, Natural Language Processing, Dependency tree, Semantic Web, federated effort for terminology building, Standard Ontology, Metadata, Systematic building of metadata, Rules for metadata, Metadata standard
Bhat, T.
, Elliott, J.
, Kattner, U.
, Campbell, C.
, Subrahmanian, E.
, Sriram, R.
, Collard, J.
and Ira, M.
(2018),
Generating Domain Terminologies using Root- and Rule-Based Terms, Journal of Washington Academy of Sciences, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=919688
(Accessed October 8, 2025)