Teaching Machines to Classify from Natural Language Interactions

Abstract

Humans routinely learn new concepts using natural language communications, even in scenarios with limited or no labeled examples. For example, a human can learn the concept of a phishing email from natural language explanations such as phishing emails often request your bank account number. On the other hand, purely inductive learning systems typically require a large collection of labeled data for learning such a concept. We believe that advances in Computational Linguistics and the growing ubiquity of computing devices together can enable people to teach computers classification tasks using natural language interactions.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2018
Accession Number
AD1168008

Entities

People

  • Shashank Srivastava

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • C4I

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Bayesian Networks
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computers
  • Information Science
  • Information Systems
  • Language
  • Machine Learning
  • Natural Language Processing
  • Neural Networks
  • Ontologies
  • Psychology
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics
  • Neural Network Machine Learning.