Monitoring Food Safety by Detecting Patterns in Consumer Complaints (2006)

Artur Dubrawski, Kimberly Elenberg, Andrew Moore, Maheshkumar Sabhnani

Tags

application, applications, bayesian, biosurveillance, early detection, emerging patterns, food safety

Abstract

EPFC (Emerging Patterns in Food Complaints) is the analytical component of the Consumer Complaint Monitoring System, designed to help the food safety officials to efficiently and effectively monitor incoming reports of adverse effects of food on its consumers. These reports, collected in a passive surveillance mode, contain multi-dimensional, heterogeneous and sparse snippets of specific information about the consumers’ demographics, the kinds, brands and sources of the food involved, symptoms of possible sickness, characteristics of foreign objects which could have been found in food, involved locations and times of occurrences, etc. Statistical data mining component of the system empowers its users, allowing for increased accuracy, specificity and timeliness of detection of naturally occurring problems as well as of potential acts of agro-terrorism. The system’s main purpose is to enhance discovery and mitigation of food borne threats to public health in the USDA Food Safety Inspection Service regulated products. As such, it is being envisioned as one of the key components of the nationwide bio-security protection infrastructure. It has been accepted for use and it is currently going through the final stages of deployment. This paper explains the motivation, key design concepts and reports the system’s utility and performance observed so far.

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Approximate BibTeX Entry

@inproceedings{IAAI0602DubrawskiA,
    Year = {2006},
    Booktitle = {Proceedings of the National Conference on Artificial Intelligence AAAI/IAAI 2006},
    Author = { Artur Dubrawski, Kimberly Elenberg, Andrew Moore, Maheshkumar Sabhnani },
    Title = {Monitoring Food Safety by Detecting Patterns in Consumer Complaints}
}