Volume : II, Issue : III, December - 2012

Data Mining for Moving Object Data

Kalpesh R. Rakholiya, Dr. Dhaval Kathiriya

Abstract :

It is easy to observe that the number of moving objects in moving objects databases like those used in transportation systems, or air traffic control centers may be very large. To achieve an acceptable level of performance with such large volumes of continuously changing data, in answering moving object queries, it is not desirable to examine the location of each moving object in the database. Indexing the location attribute is hence necessary. The widely used mechanisms for indexing spatial data, like R Trees, MVB Trees, and Quad Trees etc would not the serve the purpose well since the data in spatio–temporal applications have to be continuously updated. Movement of a point object represents the trajectory of the moving point object. Data is typically treated as a set of line segments that collectively describe the trajectory of a moving object in the database. One simplifying approach suggested in [1] is to consider indexing structures to be appendonly with respect to time.This means,data grows mainly in the temporaldimension.

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Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Kalpesh R. Rakholiya, Dr. Dhaval Kathiriya Data Mining for Moving Object Data Indian Journal of Applied Research, Vol.II, Issue.III December 2012

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