A system and method for generating a user query based on a target context aware token. The method encompasses initiating, by a processing unit [102], a search engine. The method further comprises receiving, via an input unit [104], a user input at the search engine. The method further recommends, by the processing unit [102], a set of context aware tokens based at least on the user input. Further the method encompasses selecting, by the processing unit [102], a target context aware token from the set of context aware tokens based on a user selection. The method thereafter comprises appending, by the processing unit [102], the target context aware token to the user input in the search engine. Further the method comprises generating, by the processing unit [102], the user query based on appending the target context aware token to the user input.

A radiological report editor that takes advantage of a series of templates for different types of reports. The templates provide appropriate statements which can be inserted and modified in accordance with specific observations. The statements are presented to the user in the order in which they would typically appear in a report. The statements may contain grammatically interchangeable qualifiers presented to the user in the order of historical statistical usage. A report can be based on previous reports chosen to best match the metadata of the new report, or best matching the image being reported.

A system, method and program product that provides user specific text suggestions across a set of hosted applications. A disclosed method includes: initiating a session with an application hosting platform for a user using a client device, wherein the platform includes a plurality of applications; accessing a dictionary associated with the user, wherein the dictionary provides text suggestions in response to inputted keyboard data and the dictionary is applicable for the user across each of the plurality of applications; deploying a selected application from the to the user at the client device; intercepting keyboard data entered by the user within the selected application; analyzing intercepted keyboard data and generating text suggestions specific to the user using the dictionary associated with the user; and outputting text suggestions within the selected application. The text suggestions are generated independently of capabilities of deployed application and operating systems running on the client device.

A system, method and program product that provides user specific text suggestions across a set of hosted applications. A disclosed method includes: initiating a session with an application hosting platform for a user using a client device, wherein the platform includes a plurality of applications; accessing a dictionary associated with the user, wherein the dictionary provides text suggestions in response to inputted keyboard data and the dictionary is applicable for the user across each of the plurality of applications; deploying a selected application from the to the user at the client device; intercepting keyboard data entered by the user within the selected application; analyzing intercepted keyboard data and generating text suggestions specific to the user using the dictionary associated with the user; and outputting text suggestions within the selected application. The text suggestions are generated independently of capabilities of deployed application and operating systems running on the client device.

A method for text compression comprises recognizing a prefix string of one or more text characters preceding a target string of a plurality of text characters to be compressed. The prefix string is provided to a natural language generation (NLG) model configured to output one or more predicted continuations each having an associated rank. If the one or more predicted continuations include a matching predicted continuation relative to the next one or more text characters of the target string, the next one or more text characters are compressed as an NLG-type compressed representation. If no predicted continuations match the next one or more text characters of the target string, a longest matching entry in a compression dictionary is identified. The next one or more text characters of the target string are compressed as a dictionary-type compressed representation that includes the dictionary index value of the longest matching entry.

A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. The method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model.

A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. The method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model.

Provided are techniques for generating and customizing summarized notes. A template is selected from a plurality of templates based on a context using a machine learning model. The template includes one or more translatable string resources with variables to represent key attributes extracted from historical notes. A summarized note is generated using values of the key attributes for the variables in the translatable string resources of the template.

Provided are techniques for generating and customizing summarized notes. A template is selected from a plurality of templates based on a context using a machine learning model. The template includes one or more translatable string resources with variables to represent key attributes extracted from historical notes. A summarized note is generated using values of the key attributes for the variables in the translatable string resources of the template.

A lead management system can employ a scheduling language and model for extracting appointments from consumer interactions. By using a scheduling language and model, the lead management system can accurately determine from textual content a particular time at which a consumer agreed to be called or to otherwise participate in an appointment with a representative of a business. As a result, AI-based consumer interaction agents can be utilized much more effectively to revive dead leads.