Human Factor indicators extract from accidents report

This is an exploratory study of Text Mining and it aim to identify techniques that can be used to find human factors in accident reports.
With the study output we will create a database to predict what human factors are decisive for an accident. This database can be used improve the production of oil and gas industry, and avoid accident occurring based on identified human factors. The analyzes were carried out with computational algorithms and analyzes made by humans. In this way, we reproduce in an algorithm how a human identifies certain words and phrases in a text, classify it as a human factor indicator. As a final result, the creation of a method that can identify and structure the human factors described in the HF2 model in a database is expected.

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