A system and method are provided for providing advisory notifications to mobile applications. The method includes interfacing the server device with at least one endpoint within an enterprise system and storing a model trained by a machine learning engine to automatically determine advisory notifications relevant to client data sets stored by the endpoint(s) and/or the at least one endpoint. The method also includes determining a current state of a client account, using the model to determine an advisory notification for the client account based on the current state, referring to a set of rules to determine when to provide the advisory notification in the mobile application, and in what portion of the mobile application to display the notification; and sending the advisory notification via the communications module to a client device to display the advisory notification in the mobile application.

A method for using a user-fillable form in a host container includes receiving, at a host container, a user-fillable form bound to dynamic data from an underlying data source where the user-fillable form has a data structure generated by prepopulated coding. The method further includes translating the user-fillable form into a hostable format for the host container. The method also includes rendering, using the hostable format for the host container, the user-fillable form in a user interface. The method further includes receiving, at the user interface of the host container, from a user of the host container, a data entry for input to the user-fillable form and updating, by the host container, the dynamic data from the underlying data source by persisting data from the data entry in a data store associated with the underlying data source.

According to an aspect of an embodiment, operations for detection of API compatibility across software versions are provided. The operations may include receiving an input associated with a software application. The operations may further include determining first information. The operations may further include extracting a set of data from one or more web-based sources based on the determined first information. The operations may further include executing a set of operations including one or more pattern searching operations on the extracted set of data to generate a compatibility result. The operations may further include controlling a display device based on the generated compatibility result. The display device may be controlled to display assistive information which informs about a compatibility of the one or more APIs or the functions used in the source code of the software application with respect to the second version of the software.

Methods and systems for presenting a proactive audiovisual query using a virtual assistant software application. The methods correspond to retrieving user experience data associated with a user profile for the virtual assistant software application, wherein the user experience data define one or more user experience events for the user profile. The methods further include retrieving subject matter domain data associated with the one or more user experience events, wherein the subject matter domain data define one or more probabilistic event effects for the one or more user experience events and determining, based on the user experience data and the subject matter domain data, one or more optimal query items, wherein the one or more optimal query items are associated with at least one of the one or more probabilistic event effects. The methods further include generating the proactive audiovisual query in accordance with the one or more optimal query items.

Computer implemented systems and methods are disclosed for extracting specific data using machine learning algorithms. In accordance with some embodiments, a memory device that stores at least a set of computer executable instructions for a machine learning algorithm and a pre-fill engine; and at least one processor that executes the instructions that cause the pre-fill engine to perform functions that include: receiving electronic documents, seed dataset documents, and pre-fill questions; determining output data that enable navigation through the electronic documents using the machine learning algorithm; determining output questions that enable navigation through the electronic documents using the machine learning algorithm; determining output documents to enable navigation through the electronic documents using the machine learning algorithm; and presenting one or more answers for one or more of the output questions using a graphical user interface.

In one aspect, A computerized method for implementing a virtualized training session user interface (UI) with respect to a production software UI includes the step of providing a production software application. The method includes displaying a guide on a production software UI. A workflow and a tutorial content of the guide is determined dynamically using one or more specified machine-learning algorithms. The method includes displaying the guide as a set of images with a virtual lab placed on top of each image of the guide. The method includes receiving a user input comprising a learning-related data inside a virtual environment of the guide.

In collection of training data for image recognition, in order to support a reduction in collection of improper images which are not suitable as training data, a learning data collection device includes a processor which is configured to acquire a captured image from an image capturing device, determine whether or not the captured image is suitable as training data, and when the captured image is determined to be not suitable as training data, perform a notification operation to prompt an image capturing person to reshoot a new image for the captured image.

Aspects of the subject disclosure may include, for example, a method in which a processing system generates a list of communications desired by a user, and determines an attentiveness level of the user with respect to equipment of the user currently in use, to determine whether the user is available to participate in a desired communication. The method also includes accessing equipment of a target party of the communication to determine an attentiveness level of the target party with respect to equipment of the target party, to determine whether the target party is available to participate in the communication. The method also includes generating a notice at the equipment of the user that the target party is available; and initiating the communication between the equipment of the user and the equipment of the target party. Other embodiments are disclosed.

A content transmission method is provided. The method may include: A first device determines that a distance between the first device and a second device is less than a distance threshold. The first device provides a user with a prompt that content transmission can be performed between the first device and the second device. The first device recognizes a gesture operation performed by the user on the first device, and determines transmission content and a transmission direction of the transmission content between the first device and the second device based on the recognized gesture operation. The first device receives the transmission content from the second device or sends the transmission content to the second device based on the determined transmission direction.

An apparatus includes a processor to: generate variants of an experiment design based on varied parameters; for each variant, estimate terms based on the model, and derive an optimality value; present a table of the variants including a column for each varied parameter and a column for the optimality value, a row for each variant, and a bar graph for each column depicting a distribution of the values therein; present function controls operable to select a function to perform on row(s) of the table in response to selection of a bar of a bar graph of a column; in response to selection of a function, change the current function to the selected function; and in response to a selection of a bar of a bar graph of a column, perform the current function on row(s) based on instances of the value associated with selected bar.