Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions

Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions

Shyamanta M. Hazarika (Tezpur University, India)
Release Date: May, 2012|Copyright: © 2012 |Pages: 381
DOI: 10.4018/978-1-61692-868-1
ISBN13: 9781616928681|ISBN10: 1616928689|EISBN13: 9781616928704
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Description & Coverage
Description:

Space and time are inextricably linked. Reasoning about space often involves reasoning about change in spatial configurations. Qualitative spatial information theory encompasses spatial as well as temporal representation and reasoning.

Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions is a contribution to the emerging discipline of qualitative spatial information theory within artificial intelligence. This collection of research covers both theory and application-centric research and provides a comprehensive perspective on the emerging area of qualitative spatio-temporal representation and reasoning. This revolutionary new field is increasingly becoming a core issue within mobile computing, GIS/spatial information systems, databases, computer vision as well as knowledge discovery and data mining.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Computer Vision
  • Databases
  • Distributed multi-dimensional search
  • Formal modeling of space, time and change
  • GIS/spatial information systems
  • Integrated ontologies for spatial scene descriptions
  • Knowledge discovery and data mining
  • Mobile Computing
  • Qualitative spatial modeling and reasoning
  • Spatio-temporal patterns
Reviews & Statements

Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions is a contribution to the emerging discipline of Qualitative Spatial Information Theory within Artificial Intelligence (AI). The research reported in this collection covers both theory and application-centric work in the area of qualitative spatial and temporal reasoning and provides a comprehensive perspective on the emerging area of Qualitative Spatio-Temporal Representation and Reasoning (QSTR).

– Shyamanta M. Hazarika, Tezpur University, India
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Editor/Author Biographies
Shyamanta M. Hazarika is a Professor of Computer Science and Engineering at Tezpur University. He completed his BE from Assam Engineering College, Guwhati, M.Tech in Robotics from IIT Kanpur, and PhD from University of Leeds, England. He has been a Full Professor for Cognitive Systems and NeuroInformatics at the Cognitive Systems Group, University of Bremen, Germany, for Winter 2009-2010. His work has focused primarily in knowledge representation and reasoning and rehabilitation robotics with an aim towards development of intelligent assistive systems.
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Editorial Advisory Board
  • Christian Freksa, University of Bremen, Germany
  • Amitabha Mukerjee, IIT Kanpur, India
  • Debasis Mitra, Florida Institute of Technology, USA
  • Dilip Saikia, Tezpur University, India