Automated analysis of unstructured computer text for generation of an enforcement action database using machine learning
Abstract:
Methods and apparatuses are described in which unstructured computer text is analyzed for generation of an enforcement action database. A computing device receives a digital document comprising a corpus of unstructured text and converts each sentence into tokens. The computing device identifies entities in the tokens and classifies each sentence as relevant or not relevant to an enforcement action. For each relevant sentence, the computing device generates a record in a first data structure and generates a record in a second data structure. The computing device maps the records in the first data structure to the records in the second data structure based upon an enforcement attribute to generate a third data structure. The computing device aggregates the records in the third data structure based upon a name of the entity and a type of the entity in the sentence to determine an aggregated first enforcement attribute for each entity.
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