The appraisal module is intended for email creators/donors, in collaboration with an archivist, to analyze and screeen their email for potentially sensitive, confidential, or legally protected information prior to transferring it to a repository. ePADD incorporates machine learning, natural language processing (including named entity recognition), and other functionalities (such as regular expression and advanced search) to help accomplish these goals.
Additional information can be found in documentation available through our website: http://library.stanford.edu/projects/epadd.
We'd welcome your thoughts about how ePADD might better assist you in appraising email in your collections. Please feel free to drop us a line here or via email@example.com.
ePADD Community Manager