A Noisy-Channel Approach to Question Answering

Abstract

We introduce a probabilistic noisy-channel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outperforms a state-of-the-art rule-based QA system that uses similar resources. We also show that the model we propose is flexible enough to accommodate within one mathematical framework many QA-specific resources and techniques, which range from the exploitation of WordNet, structured, and semi-structured databases to reasoning and paraphrasing.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA462242

Entities

People

  • Abdessamad Echihabi
  • Daniel Marcu

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Automated Text Summarization
  • Channel Models
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Data Sets
  • Information Science
  • Language
  • Linguistics
  • Machine Learning
  • Machine Translation
  • Natural Language Processing
  • Natural Languages
  • Probability

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Distributed Systems and Data Platform Development