A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining
DOI:
https://doi.org/10.26438/ijcse/v6i5.317324Keywords:
Spatiotemporal database, correlation analysis, features, pattern discovery, prediction, machine learning techniqueAbstract
A spatiotemporal database handles both the space and time information. A spatiotemporal database includes spatial (i.e., location and geometry of the object) and temporal data (i.e., timestamp or time interval of valid objects) where geometry of object changes over time. Spatio-temporal correlation analysis is used for identifying the spatial and temporal relationships of multiple events. The spatio-temporal objects contain number of features in pattern discovery process. However, the existing spatio-temporal pattern discovery and prediction techniques are failed to predict the future event in accurate manner and time consumption remained unaddressed. Our main objective of the research is the spatio-temporal correlation, spatio-temporal pattern discovery and prediction with higher accuracy. In order to increase the performance of spatio-temporal pattern discovery and prediction, machine learning technique are employed in our work.
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