Linguistic knowledge can improve information retrieval

  • Authors:
  • William A. Woods;Lawrence A. Bookman;Ann Houston;Robert J. Kuhns;Paul Martin;Stephen Green

  • Affiliations:
  • Sun Microsystems Laboratories, Burlington, MA;Sun Microsystems Laboratories, Burlington, MA;Sun Microsystems Laboratories, Burlington, MA;Sun Microsystems Laboratories, Burlington, MA;Sun Microsystems Laboratories, Burlington, MA;Sun Microsystems Laboratories, Burlington, MA

  • Venue:
  • ANLC '00 Proceedings of the sixth conference on Applied natural language processing
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes the results of some experiments using a new approach to information access that combines techniques from natural language processing and knowledge representation with a penalty-based technique for relevance estimation and passage retrieval. Unlike many attempts to combine natural language processing with information retrieval, these results show substantial benefit from using linguistic knowledge.