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.
Cite
@article{arxiv.1607.08580,
title = {MIST: Missing Person Intelligence Synthesis Toolkit},
author = {Elham Shaabani and Hamidreza Alvari and Paulo Shakarian and J. E. Kelly Snyder},
journal= {arXiv preprint arXiv:1607.08580},
year = {2016}
}