9 citations · 15 across the 3 of their papers we have counts for
4 papers
Safer Together: Machine Learning Models Trained on Shared Accident Datasets Predict Construction Injuries Better than Company-Specific Models
Antoine J. -P. Tixier, Matthew R. Hallowell
In this study, we capitalized on a collective dataset repository of 57k accidents from 9 companies belonging to 3 domains and tested whether models trained on multiple datasets (ge…
AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes
Henrietta Baker, Matthew R. Hallowell, Antoine J. -P. Tixier
This paper significantly improves on, and finishes to validate, an approach proposed in previous research in which safety outcomes were predicted from attributes with machine learn…
Automatically Learning Construction Injury Precursors from Text
Henrietta Baker, Matthew R. Hallowell, Antoine J. -P. Tixier
In light of the increasing availability of digitally recorded safety reports in the construction industry, it is important to develop methods to exploit these data to improve our u…
Word Embeddings for the Construction Domain
Antoine J. -P. Tixier, Michalis Vazirgiannis, Matthew R. Hallowell
We introduce word vectors for the construction domain. Our vectors were obtained by running word2vec on an 11M-word corpus that we created from scratch by leveraging freely-accessi…