Organizing Duplicate Spatio-Temporal Data in Location Intelligence
Sumeet Gill1, Meenakshi2

1Sumeet Gill, Department of Mathematics, M. D. University, Rohtak, Haryana, India.

2Meenakshi, Department of Mathematics, M. D. University, Rohtak, Haryana, India. 

Manuscript received on 05 September 2019 | Revised Manuscript received on 29 September 2019 | Manuscript Published on 29 June 2020 | PP: 433-436 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J108008810S19//2019©BEIESP | DOI: 10.35940/ijitee.J1080.08810S19

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Abstract: It has been noticed in research world in previous years that there is a huge explosion in the field of services based on location. These include applications based on location intelligence. All of these applications concentrate around process and management of data based on location and time. The amount of this kind of spatio-temporal data is increasing tremendously day by day and becoming difficult to handle, manage and query a big pile of spatio-temporal data. Because of big jumps in areas of location-aware instruments and applications depending on location, a large number of researchers are devoting their work and time towards indexing, storage and optimized retrieval of spatio-temporal data related to different areas. In this research paper, the researchers are explaining an efficient novel indexing technique to store and retrieve datasets with spatio-temporal attributes.

Keywords: Duplicate Keys, Hashing, Indexing, k-d Tree, Spatio-temporal.
Scope of the Article: Applied Mathematics and Mechanics