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Generating Domain Terminologies using Root- and Rule-Based Terms



Talapady N. Bhat, John T. Elliott, Ursula R. Kattner, Carelyn E. Campbell, Eswaran Subrahmanian, Ram D. Sriram, Jacob Collard, Monarch Ira


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
Journal of Washington Academy of Sciences


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], (Accessed May 26, 2024)


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Created December 21, 2018, Updated March 12, 2020