Assessing similarities of qualitative spatio-temporal relations

Alexander Klippel, Jinlong Yang, Jan Oliver Wallgrün, Frank Dylla, Rui Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this article we analyze behavioral data to advance knowledge on how to assess similarities of events and spatial relations characterized by qualitative spatial calculi. We have collected a large amount of behavioral data evaluating topological relations specified in the Region Connection Calculus and Intersection Models. Several suggestions have been made in the literature on how to use associated conceptual neighborhood graphs to assess the similarities between events and static spatial relations specified within these frameworks. However, to the best of our knowledge, there are few (to none) approaches that use behavioral data to formally assess similarities. This article is contributing to this endeavor of using behavioral data as a basis for similarities (and associated weights) by (a) discussing a number of approaches that allow for transforming behavioral data into numeric values; (b) applying these approaches to nine data sets we collected in the last couple of years on conceptualizing spatio-temporal information using RCC/IM as a baseline; and (c) discussing potential weighting schemes but also revealing essential avenues for future research.

Original languageEnglish (US)
Title of host publicationSpatial Cognition VIII - International Conference, Spatial Cognition 2012, Proceedings
Pages242-261
Number of pages20
DOIs
StatePublished - Nov 6 2012
EventInternational Conference on Spatial Cognition, SC 2012 - Kloster Seeon, Germany
Duration: Aug 31 2012Sep 3 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7463 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Spatial Cognition, SC 2012
CountryGermany
CityKloster Seeon
Period8/31/129/3/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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