(Almost) Automatic Semantic Feature Extraction from Technical Text

Abstract

Acquisition of semantic information is necessary for proper understanding of natural language text. Such information is often domain-specific in nature and must be acquired from the domain. This causes a problem whenever a natural language processing (NLP) system is moved from one domain to another. The portability of an NLP system can be improved if these semantic features can be acquired with limited human intervention. This paper proposes an approach towards (almost) automatic semantic feature extraction.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA460899

Entities

People

  • Rajeev Agarwal

Organizations

  • Mississippi State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Attachment
  • Automatic
  • Cataracts
  • Classification
  • Clustering
  • Computer Science
  • Diseases And Disorders
  • Extraction
  • Eye Diseases
  • Hierarchies
  • Identification
  • Intervention
  • Language
  • Mississippi
  • Veterinary Medicine

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation