MIST: Missing person Intelligence Synthesis Toolkit

Elham Shaabani, Hamidreza Alvari, Paulo Shakarian, J. E Kelly Snyder

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Each day, approximately 500 missing persons cases occur that go unsolved/unresolved in the United States. The nonprofit 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.

Original languageEnglish (US)
Title of host publicationCIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450340731
StatePublished - Oct 24 2016
Event25th ACM International Conference on Information and Knowledge Management, CIKM 2016 - Indianapolis, United States
Duration: Oct 24 2016Oct 28 2016

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Conference25th ACM International Conference on Information and Knowledge Management, CIKM 2016
Country/TerritoryUnited States


  • Abductive inference
  • Geospatial abduction
  • Law enforcement
  • Missing person

ASJC Scopus subject areas

  • General Decision Sciences
  • General Business, Management and Accounting


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