Abstract: Techniques are disclosed for automatic tagging of terms within a document and generating visual representations specifying the identifications to terms in the document and tags assigned to each term. Particularly, responsive to obtaining a document, a term auto-tagging system can implement machine learning and/or natural language processing techniques to compare terms included in the document with a database maintaining a mapping of terms and tags corresponding to each term to assign one or more tags to relevant terms. The identified terms and tags can be provided in a visual representation for processing/review at a client device, and the visual representation can be modified according to actions selected for the identified terms. The modified visual representation can be provided to a client device, and metadata for each term/tag can be uploaded to a database for training the term auto-tagging system.

Abstract: Techniques are disclosed for automatic tagging of terms within a document and generating visual representations specifying the identifications to terms in the document and tags assigned to each term. Particularly, responsive to obtaining a document, a term auto-tagging system can implement machine learning and/or natural language processing techniques to compare terms included in the document with a database maintaining a mapping of terms and tags corresponding to each term to assign one or more tags to relevant terms. The identified terms and tags can be provided in a visual representation for processing/review at a client device, and the visual representation can be modified according to actions selected for the identified terms. The modified visual representation can be provided to a client device, and metadata for each term/tag can be uploaded to a database for training the term auto-tagging system.