AAAI Publications, Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence

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Profiling and Prediction of Non-Emergency Calls in NYC
Yilong Frank Zha, Manuela Veloso

Last modified: 2014-06-18

Abstract


Non-emergency calls, namely the 311 calls, capture different complaints of city residents and visitors about a variety of experienced problems in a city. The 311 calls in New York City (NYC) are publicly available and can provide an interesting status of the city. In this paper, we share a summary of an extensive analysis that we are performing in the 311 data of NYC, as well as a data-based prediction of the number of 311 calls. We present information about the 311 data files and content along multiple dimensions, and then proceed to present prediction results, in which we show that several semantic features affect the different types of complaints differently.

Keywords


311 calls; Prediction; Random Forest

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