MIST: Missing Person Intelligence Synthesis Toolkit
release_rycmvkggdjcvngv4q7jypbbf7m
by
Elham Shaabani, Hamidreza Alvari, Paulo Shakarian, J.E. Kelly Snyder
2016
Abstract
Each day, approximately 500 missing persons cases occur that go
unsolved/unresolved in the United States. The non-profit organization known as
the Find Me Group (FMG), led by former law enforcement professionals, is
dedicated to solving or resolving these cases. This paper introduces the
Missing Person Intelligence Synthesis Toolkit (MIST) which leverages a
data-driven variant of geospatial abductive inference. This system takes search
locations provided by a group of experts and rank-orders them based on the
probability assigned to areas based on the prior performance of the experts
taken as a group. We evaluate our approach compared to the current practices
employed by the Find Me Group and found it significantly reduces the search
area - leading to a reduction of 31 square miles over 24 cases we examined in
our experiments. Currently, we are using MIST to aid the Find Me Group in an
active missing person case.
In text/plain
format
Archived Files and Locations
application/pdf 831.6 kB
file_4k7sdfmywffsfdfnzevvmteyrq
|
arxiv.org (repository) web.archive.org (webarchive) |
1607.08580v1
access all versions, variants, and formats of this works (eg, pre-prints)