Alex Klibisz
Machine learning research intern at ORNL.

Research Summary: Scalable Algorithms for Nearest Neighbor Joins on Big Trajectory Data (Feng, 2016) (Slides)

Alex Klibisz, 11/16/2016

Context: This semester (Fall 2016), I am taking a PhD-level course called Advanced Topics in Data Mining. Each week we read four published papers in the fields of data mining and machine learning. We take turns presenting on the readings so that each student will present on six of the papers through the semester.

I recently read and presented about the article Scalable algorithms for nearest-neighbor joins on big trajectory data, Fang et al., published in 2016 in 2016 IEEE 32nd International Conference on Data Engineering. The slides shared below summarize the article's key findings and techniques.

Research Summary: Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data from Alex Klibisz

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