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Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
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Generating Domain Terminologies using Root- and Rule-Based Terms.

Jacob Collard1, T N Bhat2, Eswaran Subrahmanian3,4

  • 1Independent Consultant, Ithaca, New York.

Journal. Washington Academy of Sciences, Washington, D. C
|July 1, 2021

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a method to create standardized terminology from text. This approach generates flexible, normalized terms to improve search and ontology development.

Keywords:
dependency parsingnatural language processingontology generationsearchterminology generationunsupervised learning

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Area of Science:

  • Natural Language Processing
  • Information Science
  • Computational Linguistics

Background:

  • Need for standardized terminology in search and ontology development.
  • Challenges with ambiguous and varied phrasing in natural language documents.

Purpose of the Study:

  • To present a general approach for generating flexible, reusable, and normalized terminology from natural language documents.
  • To standardize semantically similar but syntactically distinct phrases into a normal form.

Main Methods:

  • Combines linguistic and computational methods.
  • Automated extraction of normalized terms using training sets.
  • Generates root- and rule-based terms.

Main Results:

  • Successfully extracts normalized terms from natural language.
  • Ensures flexibility and evolution of terminology.
  • Reduces ambiguity and standardizes phrases.

Conclusions:

  • The approach provides a robust method for terminology generation.
  • Applicable to search, document archiving, and trend prediction.
  • Extensible with advancements in natural language technologies.