2012 DiscoveringRegionsofDifferentFu

• (Yuan et al., 2012) ⇒ Jing Yuan, Yu Zheng, and Xing Xie. (2012). “Discovering Regions of Different Functions in a City Using Human Mobility and POIs.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339561

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Cited By

• http://scholar.google.com/scholar?q=%222012%22+Discovering+Regions+of+Different+Functions+in+a+City+Using+Human+Mobility+and+POIs
• http://dl.acm.org/citation.cfm?id=2339530.2339561&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; functional regions; human mobility; spatial databases and gis; taxi trajectories; urban computing

Abstract

The development of a city gradually fosters different functional regions, such as educational areas and business districts. In this paper, we propose a framework (titled DRoF) that Discovers Regions of different Functions in a city using both human mobility among regions and points of interests (POIs) located in a region. Specifically, we segment a city into disjointed regions according to major roads, such as highways and urban express ways. We infer the functions of each region using a topic-based inference model, which regards a region as a document, a function as a topic, categories of POIs (e.g., restaurants and shopping malls) as metadata (like authors, affiliations, and key words), and human mobility patterns (when people reach / leave a region and where people come from and leave for) as words. As a result, a region is represented by a distribution of functions, and a function is featured by a distribution of mobility patterns. We further identify the intensity of each function in different locations. The results generated by our framework can benefit a variety of applications, including urban planning, location choosing for a business, and social recommendations. We evaluated our method using large-scale and real-world datasets, consisting of two POI datasets of Beijing (in 2010 and 2011) and two 3-month GPS trajectory datasets (representing human mobility) generated by over 12,000 taxicabs in Beijing in 2010 and 2011 respectively. The results justify the advantages of our approach over baseline methods solely using POIs or human mobility.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 DiscoveringRegionsofDifferentFu	Yu Zheng Jing Yuan Xing Xie			Discovering Regions of Different Functions in a City Using Human Mobility and POIs				10.1145/2339530.2339561		2012