Untangling Topic Threads in Chat-Based Communication: A Case Study

Abstract

Analyzing chat traffic has important applications for both the military and the civilian world. This paper presents a case study of a real-world application of chat analysis in support of team training exercise in the military. It compares the results of an unsupervised learning approach with those of a supervised classification approach. The paper also discusses some of the specific challenges presented by this domain.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2011
Accession Number
ADA569723

Entities

People

  • Oscar Bascara
  • Randy Jensen
  • Shaun Sucillon
  • Sowmya Ramachandran
  • Tamitha Carpenter
  • Todd Denning

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Case Studies
  • Classification
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Data Mining
  • Data Sets
  • Language
  • Machine Learning
  • Natural Language Processing
  • Natural Languages
  • Supervised Machine Learning
  • Training
  • Unsupervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Systems Analysis and Design
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation