Description

In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and

In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established.

application/pdf

Download count: 0

Details

Date Created
  • 2014-12-01
Resource Type
  • Text
  • Collections this item is in
    Identifier
    • Digital object identifier: 10.1109/TVCG.2014.2346926
    • Identifier Type
      International standard serial number
      Identifier Value
      1077-2626
    Note
    • Copyright 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Citation and reuse

    Cite this item

    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Malik, Abish, Maciejewski, Ross, Towers, Sherry, McCullough, Sean, & Ebert, David S. (2014). Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 20(12), 1863-1872. http://dx.doi.org/10.1109/TVCG.2014.2346926

    Machine-readable links