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IJBIDM
2010

Context-aware taxi demand hotspots prediction

10 years 11 months ago
Context-aware taxi demand hotspots prediction
: In an urban area, the demand for taxis is not always matched up with the supply. This paper proposes mining historical data to predict demand distributions with respect to contexts of time, weather, and taxi location. The four-step process consists of data filtering, clustering, semantic annotation, and hotness calculation. The results of three clustering algorithms are compared and demonstrated in a web mash-up application to show that context-aware demand prediction can help improve the management of taxi fleets.
Han-Wen Chang, Yu-chin Tai, Jane Yung-jen Hsu
Added 27 Jan 2011
Updated 27 Jan 2011
Type Journal
Year 2010
Where IJBIDM
Authors Han-Wen Chang, Yu-chin Tai, Jane Yung-jen Hsu
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