Algorithms for Collective Knowledge Acquisition

Abstract

Collective knowledge bases (CKBs) allow knowledge from a multitude of sources to be efficiently gathered, integrated and deployed. Markov logic provides a representation language and learning and inference algorithms for CKBs. The goal of this project was to develop solutions to several problems that need to be addressed before CKBs can be widely deployed, including: tightly coupling learning and inference, learning many levels of structure, finding complex mappings across representations, optimizing joint inference, explaining the results of inference, and accepting natural language input.

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Document Details

Document Type
Technical Report
Publication Date
May 08, 2012
Accession Number
ADA561728

Entities

People

  • Pedro Domingos

Organizations

  • University of Washington

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Artificial Intelligence
  • Computational Linguistics
  • Computer Science
  • Information Processing
  • Information Systems
  • Language
  • Linguistics
  • Logic Gates
  • Machine Learning
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • Pattern Recognition
  • Probabilistic Models
  • Probability

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML