Contribution to Project: Josh has years of experience analyzing and extracting relevant information from large volumes of textual data composed of a variety of sources and languages. He has created, curated, and maintained pivotal databases and procedures to meet the requirements of a variety of tasks including topic modeling, document clustering, and anomaly detection. His expertise gained from working in an industry where customers rely on the results of an advertised product will be very useful as this project aims to provide knowledge and understanding of the COPE-ID dataset with hopes of being extended to support any dataset of its nature in the future. Josh has created all backend functionality and integrated Elasticsearch which allows a user of the platform to search for a variety of terms, topics, and sources across millions of documents within milliseconds. He has also worked closely with Chris and Jacob to establish a normalized data structure for the documents to ensure quality and accuracy.
