Cracking Sex Trafficking: Data Analysis, Pattern Recognition, and Path Prediction-Reference-Cited by-同舟云学术

Cracking Sex Trafficking: Data Analysis, Pattern Recognition, and Path Prediction

Published:2020-12-05 Issue:4 Volume:30 Page:1110-1135
ISSN:1059-1478
Container-title:Production and Operations Management
language:en
Short-container-title:Prod Oper Manag

Author:

Keskin Burcu B.¹,Bott Gregory J.¹,Freeman Nickolas K.¹

Affiliation:

1. Department of Information Systems, Statistics, and Management Science, Culverhouse College of Business The University of Alabama Tuscaloosa Alabama 35487‐0226 USA

Publisher

Wiley

Subject

Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/poms.13294

Reference77 articles.

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2. Alvari H. P.Shakarian J.Snyder.2016.A non‐parametric learning approach to identify online human trafficking. InIEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data. Institute of Electrical and Electronics Engineers 133–138

3. Semi-supervised learning for detecting human trafficking

4. A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement

5. Bender R.2017.The Typology of Modern Slavery: Defining Sex and Labor Trafficking in the United States. Available at:https://polarisproject.org/wp‐content/uploads/2019/09/Polaris‐Typology‐of‐Modern‐Slavery‐1.pdf (accessed date February 2nd 2020).

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