Locational relativity and domain constraints in spatial questions

  • Authors:
  • Kirk Roberts;Sanda M. Harabagiu

  • Affiliations:
  • University of Texas at Dallas, Richardson TX;University of Texas at Dallas, Richardson TX

  • Venue:
  • Proceedings of the 20th International Conference on Advances in Geographic Information Systems
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Spatial queries in the form of natural language questions have typically been assumed to have unconstrained geographic answers. However, analysis of prototypical spatial questions reveals two important types of constraints that must be considered by spatial question answering systems. First, locational relativity constraints limit answers to a particular location or the user's implied location. Second, domain constraints specify non-geographic locations such as web pages or anatomical sites. In order to detect these constraints, we have conducted a crowd-sourced annotation effort for a set of over 1,200 questions gathered from a community question answering website. We utilize machine learning techniques trained on this data to automatically classify these two types of constraints. We report results nearing 90% accuracy at locational relativity detection and 76% accuracy at domain classification using this approach.