Abstract: A method performed by a computing system comprises receiving, by a hierarchical document classification system (HDCS), a document that includes image data and textual data, wherein the document is associated with a document type. The HDCS determines a first machine learning (ML) classifier of the HDCS associated with the document type. The first ML classifier corresponds to one of an image-based ML classifier of the HDCS and a text-based ML classifier of the HDCS. The determined first ML classifier classifies the document as being associated with a particular class of document of a plurality of classes of documents. A second ML classifier associated with the class of document classifies the document as being associated with a particular subclass of a plurality of subclasses of the class of document. The HDCS communicates information that specifies the class and the subclass associated with the document to a terminal.

Abstract: A method and system are used for managing and classifying electronic document images. Each of the electronic document images is divided into an array of image segments. The method extracts image features from each of the image segments to obtain numerical coefficients for each of the image segments. The numerical coefficients are compared with each other to generate sub-codes. A classification code is determined as a combination of the sub-codes. The classification codes of a plurality of electronic document images can be stored in a database for further analysis. Based on the classification codes, similarity rates between at two document images can be determined.

Abstract: Document classification techniques are disclosed that convert text content extracted from documents into graphical images and apply image classification techniques to the images. A graphical image of the text (such as a bar-code) may be generated and applied to improve the performance of document classification, bypassing NLP and utilizing more efficient localized OCR than in conventional approaches.

Abstract: A content management system categorizes electronic documents stored in a document storage database. The electronic documents include metadata. The content management system includes a categorization rules database of categorization rules. A recurrent categorization engine takes the rules and applies them to the electronic documents to generate a plurality of category groupings. Each category grouping includes groups based on the applicable rule used to create the grouping. The electronic documents are grouped between the groups. The most balanced dataset of groups is selected to generate a user prompt for further categorization of the electronic documents.

Abstract: A method is disclosed for searching electronic documents in at least one database based on user instructions entered through a user interface. A system for processing the search and calculating similarity rates of electronic documents in relation to a source electronic document is also disclosed. Electronic documents of which their similarity rates in relation to the source electronic document fall within a desired range will be selected and outputted for user's review. A computing device is in cooperation with the method and system to calculate the similarity rates.

Abstract: A method is disclosed for calculating similarity rates between electronic documents. The similarity rate is calculated based on a count of matching phrases between the electronic documents and distances between subsequent matching phrases in each of the electronic documents. A system is also disclosed for comparing the electronic documents to obtain their similarity rates. A computing device determines at least one first proximity parameter based on the number of matched words in a matching phrase and at least one second proximity parameter based on distances between the subsequent matching phrases in each of the electronic documents. The similarity rate is determined based on the first and second proximity parameters.

Abstract: A method and system are used for managing and classifying electronic document images. Each of the electronic document images is divided into an array of image segments. The method extracts image features from each of the image segments to obtain numerical coefficients for each of the image segments. The numerical coefficients are compared with each other to generate sub-codes. A classification code is determined as a combination of the sub-codes. The classification codes of a plurality of electronic document images can be stored in a database for further analysis. Based on the classification codes, similarity rates between at two document images can be determined.

Abstract: A content management system categorizes electronic documents stored in a document storage database. The electronic documents include metadata. The content management system includes a categorization rules database of categorization rules. A recurrent categorization engine takes the rules and applies them to the electronic documents to generate a plurality of category groupings. Each category grouping includes groups based on the applicable rule used to create the grouping. The electronic documents are grouped between the groups. The most balanced dataset of groups is selected to generate a user prompt for further categorization of the electronic documents.

Abstract: A system of printing devices includes an analytical server that determines when a firmware upgrade is to be installed on one or more of the printing devices. The analytical server collects information about firmware version and type along with errors that occur on the printing devices. The analytical server also collects information on the print volume for each device. A map is generated and updated based on this information that is used to decide when or if the firmware upgrade is to occur. For a first printing device and a second printing device, the analytical server determines whether to upgrade different versions of the firmware at each device.

Abstract: A method of predicting of toner replacements with logistic regression involves collecting toner level data for a print cartridge in a printing device, during a current replacement cycle of the print cartridge, at toner level data intervals, the toner level data comprising a volume percentage of toner in the print cartridge as time series level data points. The print volume data of the printing device is collected, during the current replacement cycle of the print cartridge, at a print volume data interval, the print volume data comprising a number of pages printed during the print volume data interval as time series volume data points. The toner level data and the print volume data are applied as input variables to a predetermined regression learning process. A replacement process for the print cartridge is triggered on condition that the predicted number of analytical intervals satisfies a threshold.

Abstract: Methods, systems, and storage media for characterizing print volume information for a printing asset are disclosed. Exemplary implementations may: query a first computer-readable medium having stored thereon a first print volume data; query a second computer-readable medium having stored thereon a second print volume data; perform a statistical analysis based at least on the first and second print volume data to generate a print volume statistic; code a print volume classification for storage on a data storage device; and store the print volume classification on the data storage device such that the print volume classification is accessible via a structured query.

Abstract: Methods, systems, and storage media for characterizing print volume information for a printing asset are disclosed. Exemplary implementations may: query a first computer-readable medium having stored thereon a first print volume data; query a second computer-readable medium having stored thereon a second print volume data; perform a statistical analysis based at least on the first and second print volume data to generate a print volume statistic; code a print volume classification for storage on a data storage device; and store the print volume classification on the data storage device such that the print volume classification is accessible via a structured query.

Abstract: A method performed by a computing system comprises receiving, by a hierarchical document classification system (HDCS), a document that includes image data and textual data, wherein the document is associated with a document type. The HDCS determines a first machine learning (ML) classifier of the HDCS associated with the document type. The first ML classifier corresponds to one of an image-based ML classifier of the HDCS and a text-based ML classifier of the HDCS. The determined first ML classifier classifies the document as being associated with a particular class of document of a plurality of classes of documents. A second ML classifier associated with the class of document classifies the document as being associated with a particular subclass of a plurality of subclasses of the class of document. The HDCS communicates information that specifies the class and the subclass associated with the document to a terminal.

Abstract: Methods, systems, and storage media for issuing and verifying a secondary cryptographic photo ID are disclosed. Exemplary implementations may: capture, using a scanning component of a printing device, a primary digital image of a primary photo ID; recognize, using a processing component of the printing device, alphanumeric information in the captured primary digital image; encrypt, using the processing component of the printing device, the recognized alphanumeric information; generate, using the processing component of the printing device, a digital watermark comprising the encrypted recognized alphanumeric information; recognize, using the processing component of the printing device, a photograph in the primary digital image; generate, using the processing component of the printing device, a secondary digital image comprising the recognized photograph and the generated digital watermark; and print, using a printing component of the printing device, a secondary photo ID comprising the secondary digital image.

Abstract: Document classification techniques are disclosed that convert text content extracted from documents into graphical images and apply image classification techniques to the images. A graphical image of the text (such as a bar-code) may be generated and applied to improve the performance of document classification, bypassing NLP and utilizing more efficient localized OCR than in conventional approaches.

Abstract: A system of printing devices includes an analytical server that determines when a firmware upgrade is to be installed on one or more of the printing devices. The analytical server collects information about firmware version and type along with errors that occur on the printing devices. The analytical server also collects information on the print volume for each device. A map is generated and updated based on this information that is used to decide when or if the firmware upgrade is to occur. For a first printing device and a second printing device, the analytical server determines whether to upgrade different versions of the firmware at each device.

Abstract: Methods, systems, and storage media for issuing and verifying a secondary cryptographic photo ID are disclosed. Exemplary implementations may: capture, using a scanning component of a printing device, a primary digital image of a primary photo ID; recognize, using a processing component of the printing device, alphanumeric information in the captured primary digital image; encrypt, using the processing component of the printing device, the recognized alphanumeric information; generate, using the processing component of the printing device, a digital watermark comprising the encrypted recognized alphanumeric information; recognize, using the processing component of the printing device, a photograph in the primary digital image; generate, using the processing component of the printing device, a secondary digital image comprising the recognized photograph and the generated digital watermark; and print, using a printing component of the printing device, a secondary photo ID comprising the secondary digital image.

Abstract: A system and method for enhanced workflow over email assisted by a plurality of plugins associable to a plurality of email clients is described herein. A first plugin is associable with a first email client. The first plugin is configured to write to a custom command wherein the custom command includes a machine readable message with one or more authorized actions within an email exchanged between the first email client and a second email client. A second plugin is associable with the second email client. The second plugin is configured to read from the custom command and execute the one or more authorized actions related to the second email client.

Abstract: A system of printing devices includes an analytical server that determines when a firmware upgrade is to be installed on one or more of the printing devices. The analytical server collects information about firmware version and type along with errors that occur on the printing devices. The analytical server also collects information on the print volume for each device. A map is generated and updated based on this information that is used to decide when or if the firmware upgrade is to occur. For a first printing device and a second printing device, the analytical server determines whether to upgrade different versions of the firmware at each device.

Abstract: A system of printing devices installs an upgrade version of firmware for the devices on a limited number of devices before doing a total installation. The number of the limited devices for analyzing the upgrade firmware is determined based on the failure rate of the devices. A ratio of failure is determined that is scaled by a factor to obtain the number of test devices. An analytical time interval also is determined to test the upgrade firmware on the limited number of devices. The failure rate within the limited number of devices is monitored to determine whether to upgrade all of the applicable devices.