Vijay Akkineni

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In this paper, we investigate using specifically-designated spatiotemporal indexing techniques for mining cooccurrence patterns from spatiotemporal datasets with evolving polygon-based representations. Previously, suggested techniques for spatiotemporal pattern mining algorithms did not take spatiotemporal indexing techniques into account. We present a new(More)
Mining spatiotemporal co-occurrence patterns requires assessing the strength of co-occurrences among the instances of different feature types. Currently, a spatiotemporal version of the Jaccard measure is used for measuring the strength of spatiotemporal co-occurrences. We present an extended spatiotemporal version of the Jaccard measure (<i>J*</i>) that is(More)
Moving object prediction and indexing have been a well studied area of research and include applications in environment monitoring, traffic prediction, advertising, and efficient routing. Spark is a cluster computing framework, which utilizes Resilient Distributed Datasets (RDD) on a cluster of several commodity machines. Spark is popularly used for(More)
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