Dynamic and Supervised Topic Models for Literature-Based Discovery

Abstract

Under the support of the ONR my research focused on extending the state ot the an or probabilistic topic modeling, algorithms for making discoveries from and predictions about large collections of texts. For the past three years, my group has published many papers in the service of this goal. In this report, I will highlight some of the themes and publications that represent this work. Thanks to the support of the ONR, we have made excellent progress in our stated goals.

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Document Details

Document Type
Technical Report
Publication Date
Dec 21, 2011
Accession Number
ADA554210

Entities

People

  • David M. Blei

Organizations

  • Princeton University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Computations
  • Computer Science
  • Data Sets
  • General Relativity
  • Information Operations
  • Instructions
  • Language
  • Literature
  • Military Research
  • Natural Language Processing
  • Natural Languages
  • New York
  • Open Source Software
  • Social Media

Readers

  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design