Wells Fargo Bank, N.a.

Maria Chiarenza

Debashis Ghosh

Matthew C Howell

Nathaniel D Mollison

Systems, apparatuses, methods, and computer program products are disclosed for obtaining relevant data from an unstructured data source. An example method includes extracting relevant data that is intermixed with extraneous data using natural language processing. In order to do so, text from the unstructured data source may be tokenized and each token may be compared to an identifier associated with the relevant data. A similarity metric may be determined between each token and the identifier in order to classify tokens as similar or dissimilar to the identifier. All tokens classified as similar to the identifier may be aggregated in order to obtain relevant data.

System and methods for classification of unstructured data using similarity metrics

Systems, apparatuses, methods, and computer program products are disclosed for obtaining data. The data may be obtained from a variety of data sources. In order to determine the preferred data source for obtaining the data, data quality scores may be computed and assigned to each data source of interest for a given implementation. Each data quality score may take into account several criteria including the computing resources required to obtain the data, the financial cost of obtaining the data, the security risk of obtaining the data, etc. Data may be obtained from the preferred data source, presented to a user associated with the data for verification, and processed in order to provide a computer-implemented services to the user.

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Indian Trail, NC, United States of America

Maria Chiarenza