Auto-detection of safety issues in baby products

Graham Bleaney, Matthew Kuzyk, Julian Man, Hossein Mayanloo, H. R. Tizhoosh

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


Every year, thousands of people receive consumer product related injuries. Research indicates that online customer reviews can be processed to autonomously identify product safety issues. Early identification of safety issues can lead to earlier recalls, and thus fewer injuries and deaths. A dataset of product reviews from was compiled, along with complaints and recall descriptions from the Consumer Product Safety Commission (CPSC) and European Commission Rapid Alert system. A system was built to clean the collected text and to extract relevant features. Dimensionality reduction was performed by computing feature relevance through a Random Forest and discarding features with low information gain. Various classifiers were analyzed, including Logistic Regression, SVMs, Naïve-Bayes, Random Forests, and an Ensemble classifier. Experimentation with various features and classifier combinations resulted in a logistic regression model with 70.2% precision in the top 50 reviews surfaced. This classifier outperforms all benchmarks set by related literature and consumer product safety professionals.

Original languageEnglish (US)
Title of host publicationRecent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Proceedings
EditorsOtmane Ait Mohamed, Malek Mouhoub, Samira Sadaoui, Moonis Ali
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319920573
StatePublished - 2018
Event31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018 - Montreal, Canada
Duration: Jun 25 2018Jun 28 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10868 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018


  • Machine learning
  • Online reviews
  • Product safety
  • Text mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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