Abstract: A data processing system obtains source textual content associated with a first writing style and target textual content associated with a second writing style and provides the source textual content as an input to a first machine learning model which analyzes the source content to determine the first writing style of the first textual content. The system provides an indication of the first writing style and the target textual content as an input to a second machine learning model which analyzes the target textual content and rewrites the target textual content according to the first writing style to output updated target textual content rewritten according to the first writing style. Some implementations utilize a single model trained to receive the source textual content, the target textual content, to determine the writing style of the source textual content and rewrite the target textual content according to the first writing style.

Abstract: A system and method for generating a document control item is described. The system accesses a text document and extracts a portion of the text document. The portion comprises some but not all of the text document. The system sends the portion of the text document to a trained machine learning model and, in response, receives a classification of the portion as demarking a section break. The system modifies the text document by inserting a document control item into the text document at a location of each portion classified as demarking a section break. The system stores the modified document.

Abstract: A system and method for automatically generating help documentation for an application includes examining telemetry data associated with a plurality of users' use of the application and identifying from the telemetry data an intended action for which a help documentation should be generated. Upon identifying the intended action, an action path in the application for arriving at the intended action may be determined where the action path includes one or more actions taken before arriving at the intended action and an action label for each of the actions may be identified. The action path and the action label may be provided to a trained machine-learning (ML) model for automatically generating the help documentation and in response, an automatically generated help documentation may be received as an output.

Abstract: A system and method for converting a document is described. The system accesses a document comprising one or more section breaks. The system detects sections of the text document demarked by the one or more section breaks and generates a section title metadata and a section summary metadata for each section of the plurality of sections. The system inserts the section title metadata and the section summary metadata at the corresponding section breaks in the text document. The system modifies the text document into slides. Each slide being formed for each section based on the corresponding section title metadata and the section summary metadata. The system generates a presentation document based on the slides.

Abstract: A system and method and for generating a template based on a page of a document includes receiving a request to create the template for the document, providing a page of the document as an input to a trained machine-learning (ML) model, where the trained machine-learning model is trained to automatically generate target pages for the document based on a received page and the page includes a background image and content, and receiving target pages for the document from the ML model. Each target page has a distinct layout and includes a modified background image and one or more placeholders for content and a template for the document is generated from the one or more target pages and provided for display on a user interface screen associated with the document.

Abstract: A method and system for providing tone detection for a content may include receiving a request to detect a tone for a content, retrieving user data and data about the content, detecting a content environment for the content based on at least one of the user data and the data about the content, detecting the tone for the content based on the content and the content environment, inputting the content and the detected tone into a machine-learning (ML) model for modifying the tone from the detected tone to a modified tone, obtaining at least one rephrased content segment as an output from the ML model, the rephrased content segment modifying the tone of the content from the detected tone to the modified tone, and providing at least one of the detected tone or the at least one rephrased content segment for display.

Abstract: A system and method and for monitoring an online meeting includes receiving an indication that the online meeting has been started, retrieving meeting metadata associated with the online meeting, meeting content data from the online meeting, and user data associated with one or more meeting invitees; providing at least one of the meeting metadata, meeting content data and the user data to a machine-learning model for detecting a meeting stage for the online meeting in real-time, determining and based on at least one of the detected meeting stage, meeting content data or the user data that a notification about the online meeting should be provided to one of the meeting invitees, generating data for the notification, and providing the data for the notification for display to the meeting invitee.

Abstract: A system and method and for monitoring an online meeting includes receiving an indication that the online meeting has been started, retrieving meeting metadata associated with the online meeting, meeting content data from the online meeting, and user data associated with one or more meeting invitees; providing at least one of the meeting metadata, meeting content data and the user data to a machine-learning model for detecting a meeting stage for the online meeting in real-time, determining and based on at least one of the detected meeting stage, meeting content data or the user data that a notification about the online meeting should be provided to one of the meeting invitees, generating data for the notification, and providing the data for the notification for display to the meeting invitee.

Abstract: Technologies are provided for automated generation of revision summaries for an electronic document. In some embodiments, a computing system can determine that a first section of a first version of the electronic document includes changes relative to a second section of a second version of the electronic document. The second section corresponds to the first section. The computing system also can generate respective descriptions of the first section and the second section. The computing system can then generate a summary of the changes by comparing the respective descriptions. The computing system can determine that the summary has a defined placement in a ranking of similarity scores, where a first similarity score in the ranking defines similarity between the respective descriptions. The computing system can add metadata to the first version of the electronic document. The metadata controls presentation of a visual element indicative of the summary within a user interface.

Abstract: A system and method for generating a document control item is described. The system accesses a text document and extracts a portion of the text document. The portion comprises some but not all of the text document. The system sends the portion of the text document to a trained machine learning model and, in response, receives a classification of the portion as demarking a section break. The system modifies the text document by inserting a document control item into the text document at a location of each portion classified as demarking a section break. The system stores the modified document.

Abstract: Technologies are provided for automated generation of revision summaries for an electronic document. In some embodiments, a computing system can determine that a first section of a first version of the electronic document includes changes relative to a second section of a second version of the electronic document. The second section corresponds to the first section. The computing system also can generate respective descriptions of the first section and the second section. The computing system can then generate a summary of the changes by comparing the respective descriptions. The computing system can determine that the summary has a defined placement in a ranking of similarity scores, where a first similarity score in the ranking defines similarity between the respective descriptions. The computing system can add metadata to the first version of the electronic document. The metadata controls presentation of a visual element indicative of the summary within a user interface.

Abstract: A system and method for personalizing a display of a recommendation in a user interface element of an application is described. The system accesses application activities of a user of the application. A user preference is formed based on the application activities. The system identifies a context of a current activity of the application and generates a content recommendation in the application based on the context of the current activity of the application and the user preference.

Abstract: Systems and methods for classifying content of an electronic file. One system includes an electronic processor configured to determine a content type associated with a portion of content included in the electronic file using a classification model developed using machine learning. The electronic processor is also configured to determine a suggested modification for the portion of content based on the determined content type. The suggested modification is a modification to a format property of the portion of content. The electronic processor is also configured to provide a notification of the suggested modification to a user for acceptance of the suggested modification. In response to the user accepting the suggested modification, the electronic processor is configured to modify the format property of the portion of content in accordance with the suggested modification.

Abstract: Systems and methods directed to providing recommended charts are provided. More specifically, a selection of data arranged in a plurality of data series may be received and classified into series data types. Based on the series data type for each data series of the plurality of data series, a plurality of recommended charts visually describing the data may be automatically provided to a user interface, wherein each chart of the plurality of recommended charts is a different chart type visually describing the data. To provide the plurality of recommended charts, best practices and/or one or more machine learning models may be utilized. In some instances, the charts provided in the user interface may automatically change or otherwise updated based on a different selection of data and/or an assignment of a different data series type to a data series.

Abstract: A process for improving dispatch of different types of law enforcement patrols (LEPs) for achieving a desired deterrent effect includes first receiving patrol route information indicating patrol routes taken by first LEPs, and then determining, as a function of a type of each of the first LEPs, a threshold level of deterrence reached for each of the patrol routes taken. Subsequently, a threshold level of deterrence desired (TLoDD) for each of the plurality of patrol routes is determined as a function of historical and/or real-time crime information. A first patrol route having a threshold level of deterrence reached (TLoDR) that is less than a TOoDD is identified and, as a function of the difference, a particular type of second LEP having a sufficient deterrent effect factor to compensate for the difference is identified. An available responding second LEP of the particular type is then identified for dispatch.

Abstract: A method and apparatus for providing a virtual push-to-talk (PTT) button is provided herein. During operation, an augmented reality and object recognition circuitry will detect user's fingers and a free surface near the fingers by analyzing image captured by camera. A virtual PTT button is placed upon an object that is near to user's finger. Gesture recognition will be performed by the circuitry to determine if a user presses the virtual PTT button. When a user presses the virtual PTT button, the circuitry identifies the action and transmits a message to a PTT radio, causing the PTT radio to activate a PTT call.

Abstract: A process for displaying crime deterrent effects includes first receiving patrol route information indicating a patrol route taken by a law enforcement patrol and determining a type of the law enforcement patrol. Subsequently, a deterrent effect parameter associated with the law enforcement patrol is determined as a function of the determined type of the law enforcement patrol. Finally, an electronic display is caused to display a cartographic map of a geographic area at least partially including the patrol route taken by the law enforcement patrol and, along the patrol route taken, to display a deterrent effect indicator having a radius, width, size, and/or fade time that varies as a function of the type of the determined deterrent effect parameter.

Abstract: A method and apparatus for providing a virtual push-to-talk (PTT) button is provided herein. During operation, an augmented reality and object recognition circuitry will detect user's fingers and a free surface near the fingers by analyzing image captured by camera. A virtual PTT button is placed upon an object that is near to user's finger. Gesture recognition will be performed by the circuitry to determine if a user presses the virtual PTT button. When a user presses the virtual PTT button, the circuitry identifies the action and transmits a message to a PTT radio, causing the PTT radio to activate a PTT call.

Abstract: A process for improving dispatch of different types of law enforcement patrols (LEPs) for achieving a desired deterrent effect includes first receiving patrol route information indicating patrol routes taken by first LEPs, and then determining, as a function of a type of each of the first LEPs, a threshold level of deterrence reached for each of the patrol routes taken. Subsequently, a threshold level of deterrence desired (TLoDD) for each of the plurality of patrol routes is determined as a function of historical and/or real-time crime information. A first patrol route having a threshold level of deterrence reached (TLoDR) that is less than a TOoDD is identified and, as a function of the difference, a particular type of second LEP having a sufficient deterrent effect factor to compensate for the difference is identified. An available responding second LEP of the particular type is then identified for dispatch.

Abstract: A process for displaying crime deterrent effects includes first receiving patrol route information indicating a patrol route taken by a law enforcement patrol and determining a type of the law enforcement patrol. Subsequently, a deterrent effect parameter associated with the law enforcement patrol is determined as a function of the determined type of the law enforcement patrol. Finally, an electronic display is caused to display a cartographic map of a geographic area at least partially including the patrol route taken by the law enforcement patrol and, along the patrol route taken, to display a deterrent effect indicator having a radius, width, size, and/or fade time that varies as a function of the type of the determined deterrent effect parameter.