Moving Region in Spatial Temporal Data Warehousing
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Jiawei Han and Micheline Kamber “Data Mining Concepts and Techniques”, second edition, Morgan Kaufmann Publishers an imprint of Elsevier
Taher Omran Ahmed and Maryvonne Miquel “ Multidimensional Structures Dedicated to Continuous Spatiotemporal Phenomena “ Springer-Verlag Berlin Heidelberg 2005, pp 1-12
Dimitris Papadias, Yufei Tao, Panos Kalnis, Jun Zhang, "Indexing Spatio-Temporal Data Warehouses," Data Engineering, International Conference 2002
Kimball, R. “The Data Warehouse Toolkit” John Wiley, 1996.
Ghazi h. Al-naymat “new methods for mining Sequential and time series Data”, PhD thesis, the university of Sydney June 2009
Anthony David Veness “A real-time spatio-temporal data exploration tool for marine research”, Master of Applied Science University of Tasmania, October 2009.
S.Sudarsan Krithiramamritham “Data Warehousing and Data mining”, IIT Bombay, sudarsha@ cse.iitb.ernet.in,krithi@cse.iitb.ernet.in
Subramanian Arumugam “efficient algorithms for spatiotemporal data management”, PhD Thesis University of Florida, 2008
M. Pelanis, S. ˇ Saltenis, and C. Jensen. Indexing the past, present 1`2and anticipated future positions of moving objects. TODS, 31(1):255–298, 2006.
Z.-H. Liu, X.-L. Liu, J.-W. Ge, and H.-Y. Bae. Indexing large moving objects from past to future with PCFI+-index.In COMAD, pages 131–137, 2005.
D. Lin, C. Jensen, B. Ooi, and S. Saltenis. “Efficient indexing of the historical, present, and future positions of moving objects. In MDM, pages 59–66, 2005.
N. Roussopoulos, S. Kelley, F. Vincent, "Nearest neighbour Queries", Proceedings of ACM SIGMOD Conference, 1995.
Ralf Hartmut Guting and Markus Schneider “Moving Objects Databases”, Elsevier publication, 2005
The website of http://weather.unisys.com/hurricane/.
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