Systems and methods for location threat monitoring

A location threat monitoring system, comprising:

• a processor;
• a non-transitory computer-readable medium;
• and
• stored instructions translatable by the processor for:
• obtaining or receiving, from a data source, data containing textual information relating to a brand;
• providing the textual information to a deep learning (DL) model specifically built for processing the data from the data source, the DL model comprising an artificial neural network (ANN), the ANN trained, using sample data sets from the data source, to recognize or infer whether a piece of natural language input data references an address or location of interest to the brand, regardless of whether the piece of natural language input data actually contains the address or location;
• determining, by comparing an outcome from the ANN with a threshold, whether the data from the data source is to be classified for potential location threats, the outcome from the ANN comprising a probability score that the data from the data source references an address or location of interest to the brand;
• and
• responsive to the probability score from the ANN meeting or exceeding the threshold, providing the data from the data source to location threat classifiers, wherein the location threat classifiers are operable to identify a location threat with respect to the address or location referenced in the data from the data source.

A computer program product for location threat monitoring, the computer program product comprising a non-transitory computer-readable medium storing instructions translatable by a processor for:

• obtaining or receiving, from a data source, data containing textual information relating to a brand;
• providing the textual information to a deep learning (DL) model specifically built for processing the data from the data source, the DL model comprising an artificial neural network (ANN), the ANN trained, using sample data sets from the data source, to recognize or infer whether a piece of natural language input data references an address or location of interest to the brand, regardless of whether the piece of natural language input data actually contains the address or location;
• determining, by comparing an outcome from the ANN with a threshold, whether the data from the data source is to be classified for potential location threats, the outcome from the ANN comprising a probability score that the data from the data source references an address or location of interest to the brand;
• and
• responsive to the probability score from the ANN meeting or exceeding the threshold, providing the data from the data source to location threat classifiers, wherein the location threat classifiers are operable to identify a location threat with respect to the address or location referenced in the data from the data source.