CS 260: Seminar on Spatial and Spatiotemporal Databases


Course Description:

In this course, we will discuss various issues arising in the context of the management of spatial and spatiotemporal data. We will look exclusively at readings from the research literature.

Prerequisites:

Students must have taken a course in data bases.

Class times:

Tuesdays & Thursdays 12:40pm - 2:00pm. The class meets in WCH 139.

Office hours:

By appointment. Tel: 827-5318 E-mail: ravi@cs.ucr.edu.

Grading:

Class participation: 40%, project: 60%.

Papers



  • Antonin Guttman: R-Trees: A Dynamic Index Structure for Spatial Searching. SIGMOD Conference 1984: 47-57, R-tree.pdf
  • Efficient Processing of Spatial Joins Using R-Trees
  • Spatial Joins Using Seeded Trees
  • Spatial Hash Joins
  • Indexing Methods for Moving Object Databases: Games and Other Applications
  • UV-diagram: a voronoi diagram for uncertain spatial databases
  • Continuous Intersection Joins Over Moving Objects
  • Processing of extreme moving-object update and query workloads in main memory
  • Elite: an elastic infrastructure for big spatiotemporal trajectories
  • Efficient Anomaly Monitoring Over Moving Object Trajectory Streams
  • PIST: An Efficient and Practical Indexing Technique for Historical Spatio-Temporal Point Data
  • Robust and Fast Similarity Search for Moving Object Trajectories
  • A query integrity assurance scheme for accessing outsourced spatial databases
  • Blind evaluation of location based queries using space transformation to preserve location privacy
  • Mining, Indexing, and Querying Historical Spatiotemporal Data
  • Speed Partitioning for Indexing Moving Objects
  • Spatiotemporal Data Mining: A Computational Perspective
  • Primal or Dual: Which Promises Faster Spatiotemporal Search?
  • The Bdual-Tree: indexing moving objects by space filling curves in the dual space
  • Using Efficient Polynomial Approximations for Spatiotemporal Trajectories