2012 ConstructingPopularRoutesfromUn

• (Wei et al., 2012) ⇒ Ling-Yin Wei, Yu Zheng, and Wen-Chih Peng. (2012). “Constructing Popular Routes from Uncertain Trajectories.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339562

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Cited By

• http://scholar.google.com/scholar?q=%222012%22+Constructing+Popular+Routes+from+Uncertain+Trajectories
• http://dl.acm.org/citation.cfm?id=2339530.2339562&preflayout=flat#citedby

Quotes

Author Keywords

• Collaborative learning; data mining; route inference; social media; spatial databases and gis; trajectory data mining

Abstract

The advances in location-acquisition technologies have led to a myriad of spatial trajectories. These trajectories are usually generated at a low or an irregular frequency due to applications' characteristics or energy saving, leaving the routes between two consecutive points of a single trajectory uncertain (called an uncertain trajectory). In this paper, we present a Route Inference framework based on Collective Knowledge (abbreviated as RICK) to construct the popular routes from uncertain trajectories. Explicitly, given a location sequence and a time span, the RICK is able to construct the top-k routes which sequentially pass through the locations within the specified time span, by aggregating such uncertain trajectories in a mutual reinforcement way (i.e., uncertain + uncertain → certain). Our work can benefit trip planning, traffic management, and animal movement studies. The RICK comprises two components: routable graph construction and route inference. First, we explore the spatial and temporal characteristics of uncertain trajectories and construct a routable graph by collaborative learning among the uncertain trajectories. Second, in light of the routable graph, we propose a routing algorithm to construct the top-k routes according to a user-specified query. We have conducted extensive experiments on two real datasets, consisting of Foursquare check-in datasets and taxi trajectories. The results show that RICK is both effective and efficient.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 ConstructingPopularRoutesfromUn	Yu Zheng Ling-Yin Wei Wen-Chih Peng			Constructing Popular Routes from Uncertain Trajectories				10.1145/2339530.2339562		2012