R2-D2: a System to Support Probabilistic Path Prediction in Dynamic Environments via "Semi-Lazy" Learning

Summary: R2-D2 enables probabilistic path prediction in dynamic environments with a semi-lazy learning approach that builds an on-the-fly model from selectively chosen trajectories. A visual interface demonstrates the method and enables real-time parameter tuning on datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10616
Venue: VLDB
Year: 2013
Pagerank: 4.1945683e-05
Overall Rank: 12,080 | 15.97%
DOI: -

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,921	SMiLer: A Semi-Lazy Time Series Prediction System for Sensors	2015	SIGMOD	4.1945683e-05

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2,889	Prediction and Indexing of Moving Objects with Unknown Motion Patterns	2004	SIGMOD	7.9587247e-05

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