Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Mining 911 calls in New York City : temporal patterns, detection and forecasting

Tools
- Tools
+ Tools

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.

[img]
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:
DateEvent
2015Created
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 View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us