Chohlas-Wood, Alex , Merali, Aliya , Reed, Warren and Damoulas, Theodoros (2015) Mining 911 calls in New York City : temporal patterns, detection and forecasting. In: 29th AAAI Conference on Artificial Intelligence, (AAAI 2015), Austin, Texas USA , 25–26 Jan 2015 pp. 4-10.

Preview

PDF WRAP_1472826-cs-100416-aaai15_911damoulas.pdf - Published Version - Requires a PDF viewer. Download (4008Kb) | Preview

Request Changes to record.

Abstract

The New York Police Department (NYPD) is tasked with responding to a wide range of incidents that are reported through the city’s 911 emergency hotline. Currently, response resources are distributed within police precincts on the basis of high-level summary statistics and expert reasoning. In this paper, we describe our first steps towards a better understanding of 911 call activity: temporal behavioral clustering, predictive models of call activity, and anomalous event detection. In practice, the proposed techniques provide decision makers granular information on resource allocation needs across precincts and are important components of an overall data-driven resource allocation policy.

Item Type:	Conference Item (Paper)
Subjects:	H Social Sciences > HE Transportation and Communications
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH):	Telephone -- Emergency reporting systems
Official Date:	2015
Dates:	Date Event 2015 Created
Page Range:	pp. 4-10
Status:	Peer Reviewed
Publication Status:	Published
Date of first compliant deposit:	18 April 2016
Date of first compliant Open Access:	19 April 2016
Conference Paper Type:	Paper
Title of Event:	29th AAAI Conference on Artificial Intelligence, (AAAI 2015)
Type of Event:	Conference
Location of Event:	Austin, Texas USA
Date(s) of Event:	25–26 Jan 2015

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads