Abstract: One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: receiving an underlying standard; extracting conceptual units from the underlying standard; classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups; storing the classified extracted conceptual units into a data repository as defined by the schema; displaying, within a user interface on a display of an information handling device, a digital standard in a format based upon the schema; and providing, within the user interface, search and filter functions allowing for finding information related to the digital standard. Other aspects are described and claimed.

Abstract: One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: receiving an underlying standard; extracting conceptual units from the underlying standard; classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups, wherein each of the classification groups identifies a function of the extracted conceptual units, included within a given classification group, within the underlying standard; wherein the classifying comprises classifying conceptual units from the underlying standard based upon sections of a schema corresponding to a digital standard; and storing the classified extracted conceptual units into a data repository based upon the schema. Other aspects are described and claimed.

Abstract: One embodiment provides a method for graphically displaying and interacting with digital standards, the method including: displaying, on an interactive display, a digital standard interface display for displaying and interacting with information corresponding to at least one digital standard, wherein the digital standard interface display comprises a plurality of icons that are selectable by a user; wherein at least one of the plurality of icons comprises a standards category icon for displaying information related to digital standards within a category corresponding to the standards category icon; displaying a digital standard selection field in response to a user selection of one of the standards category icons; and displaying, responsive to a user providing input to the digital standard selection field, information related to a digital standard identified from the provided input and of the category type corresponding to the selected standards category icon. Other aspects are described and claimed.

Abstract: One embodiment provides a method for identifying similar objects by performing document attribute comparisons, the method including: receiving a reference document, wherein the reference document corresponds to an object and comprises a plurality of attributes of the object; receiving a request for a similarity comparison, wherein the request provides an indication of similarity attributes to be used in the similarity comparison; comparing the reference document to each of a plurality of documents corresponding to other objects; generating a document similarity score for each of the plurality of documents, wherein the document similarity score is generated based upon an aggregation of similarity attribute scores calculated for each of the similarity attributes; and providing at least one of the plurality of documents with an indication of a similarity. Other aspects are described and claimed.

Abstract: Provided are systems and methods that allow a user to capture images at low- and high-level magnification and then overlay the high-level magnification images on the low-level magnification image to ease review of the images. The high-level magnification images may be overlaid on the low-level magnification image based at least in part on the portion of the low-level magnification image from which the high-level image was originated.

Abstract: One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: receiving an underlying standard; extracting conceptual units from the underlying standard; classifying, using at least one trained machine-learning model, at least a portion of the extracted conceptual units into one of a plurality of classification groups, wherein each of the classification groups identifies a function of the extracted conceptual units, included within a given classification group, within the underlying standard; wherein the classifying comprises classifying conceptual units from the underlying standard based upon sections of a schema corresponding to a digital standard; and storing the classified extracted conceptual units into a data repository based upon the schema. Other aspects are described and claimed.

Abstract: One embodiment provides a method for graphically displaying and interacting with digital standards, the method including: displaying, on an interactive display, a digital standard interface display for displaying and interacting with information corresponding to at least one digital standard, wherein the digital standard interface display comprises a plurality of icons that are selectable by a user; wherein at least one of the plurality of icons comprises a standards category icon for displaying information related to digital standards within a category corresponding to the standards category icon; displaying a digital standard selection field in response to a user selection of one of the standards category icons; and displaying, responsive to a user providing input to the digital standard selection field, information related to a digital standard identified from the provided input and of the category type corresponding to the selected standards category icon. Other aspects are described and claimed.

Abstract: Provided are systems and methods that allow a user to capture images at low- and high-level magnification and then overlay the high-level magnification images on the low-level magnification image to ease review of the images. The high-level magnification images may be overlaid on the low-level magnification image based at least in part on the portion of the low-level magnification image from which the high-level image was originated.