SRC15. Touring Dataland? Automated Recommendations for the Big Data Traveler
Author
Event Type
ACM Student Research Competition
Poster
LocationExhibit Hall E, Booth #104
DescriptionWe explore how recommendation techniques can be adapted and applied to big data science. Using features specific to big data science, we develop a set of data location prediction heuristics. We combine these heuristics into a single recommendation engine using a deep recurrent neural network. We show, via analysis of historical Globus operations, that our approaches can predict the storage locations accessed by users with 78.2% and 95.5% accuracy for top-1 and top-3 recommendations, respectively.
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