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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Topological Feature Mining for Rambling Activities
verfasst von : Masakatsu Ohta, Miyuki Imada
Erschienen in: Contemporary Challenges and Solutions in Applied Artificial Intelligence
Verlag: Springer International Publishing
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A method for investigating rambling activities of moving objects is proposed. The goal is to construct common metrics used in various environments for characterizing the trajectory followed by rambling objects. Rambling activities are multi-stop,multi-purpose trips with trajectories with many intersections.Mathematical knot theory is introduced to examine the topological relation between intersections. The trajectories in an environment are represented in a vector space consisting of prime knots. Like a prime number, a prime knot is universal; thus, it is possible to compare the features of rambling activities across environments. An experiment using real-world taxi trajectories demonstrated that our method effectively classifies rambling activities according to daytime, nighttime, and a special event.