Abstract: Techniques for updating a sentiment analysis model in response to feedback for operations that are executed based on an output of the sentiment analysis model are disclosed. The sentiment analysis model analyzes a chat conversation to determine user sentiment. The system executes an operation based on the user sentiment determined by the sentiment analysis model. The operation may be the transfer of the chat conversation from a chatbot to a human agent or the generation of an outbound message by the chatbot. The system receives positive or negative feedback regarding the appropriateness and/or timeliness of the operation. The positive or negative feedback is attributed to the sentiment analysis model. The system generates training data using the feedback. The system then retrains the sentiment analysis model based on the training data.

Abstract: Techniques for configuring one or more applications based on a detected wakefulness state of a user are disclosed. A system trains and applies a machine learning model to wakefulness data to compute a wakefulness state of a user. The system obtains the wakefulness data from wearable devices worn by the user and environmental devices in a user's environment. The system configures applications and/or devices based on the computed wakefulness state of the user. The system configures the ability of devices or applications to generate visual, audible, or tactile notifications in response to determining that a user is awake or asleep.

Abstract: Techniques for drilling back to an original audio clip in virtual assistant initiated lists and reminders are disclosed. The system may receive audio input comprising a first request. Based on the first request, the system may schedule an action to be performed by the virtual assistant platform. The system stores at least a portion of the audio input and a mapping between the action and at least the portion of the audio input. The system performs the action. Subsequent to performing the action, the system receives a second request for audio playback of the first request corresponding to the action. The system retrieves at least the portion of the audio input based on the mapping between the action and at least the portion of the audio input, and plays at least the portion of the audio input comprising the first request.

Abstract: Systems, methods, and computer-readable media are provided for generating an interactive node graph showing process states. A data management system accesses a data structure that includes a set of candidate process records representing a plurality of candidate process states, where each candidate process record represents a candidate process state and one or more sequentially connected candidate process states. The data management system generates an interactive node graph that includes nodes, each node representing a candidate process state. The interactive node graph includes edges representing candidate connections between candidate process states. The data management system causes display of the interactive node graph. The data management system receives input modifying settings for displaying the interactive node graph and causes display of an updated interactive node graph using the settings as modified.

Abstract: Systems and methods and computer-readable media are provided for generating an interactive node graph showing aggregate node and/or edge metrics. The interactive node graph includes nodes and edges, each representing a process state or a connection between process states. The data management system marks each node graphically based on a first metric type that is based on an aggregation of occurrences of a corresponding process state and marks each edge graphically based on a second metric type that is based on an aggregation of occurrences of a transition between corresponding process states. The data management system causes display of the interactive node graph, receives input modifying a particular metric type of the first metric type or the second metric type, and causes display of an updated interactive node graph based at least in part on the particular metric type as modified.

Abstract: Systems, methods, and computer-readable media are provided for animating an interactive node graph. A data management system generates an interactive node graph having nodes that represent process states and edges representing connections between process states. The data management system uses a first live metric for determining aggregated node values and a second live metric to use for determining aggregated edge values. The data management system causes display of the interactive node graph according to a selected data slice of a plurality of data slices. Based at least in part on a selection of an option to play the interactive node graph through the plurality of data slices, the data management system updates the display of the interactive node graph to show a different data slices of the plurality of data slices, and, after an amount of time, another different data slice of the plurality of data slices.

Abstract: Systems, methods, and computer-readable media are provided for storing a snapshot of an interactive node graph. A data management system generates an interactive node graph having nodes that represent process states and edges representing connections between process states. The data management system uses a first live metric for determining aggregated node values and a second live metric to use for determining aggregated edge values. Based at least in part on a selection of an option to save the interactive node graph, the data management system stores a snapshot. The snapshot includes the aggregated node values based on the first live metric as of a particular time, the aggregated edge values based on the second live metric as of the particular time, a first mapping between the first live metric and the nodes, and a second mapping between the second live metric and the edges.

Abstract: A system manager is disclosed for automatically deploying software based on user activity. The system manager receives user-specified parameters to control whether, when, and/or how automatic deployment is performed for software components, without specifying which software components are to be automatically deployed for the user. The system manager stores software component metadata identifying software components that are available for deployment. The system manager analyzes user activity to determine autodeployment utility scores that predict degrees of utility for different software components. Based on determining that an autodeployment utility score for a candidate software component satisfies one or more conditions that are based on the user-specified parameters, the system manager automatically performs deployment operation(s) for the candidate software component in a computing environment of a user.

Abstract: Techniques for updating a sentiment analysis model in response to feedback for operations that are executed based on an output of the sentiment analysis model are disclosed. The sentiment analysis model analyzes a chat conversation to determine user sentiment. The system executes an operation based on the user sentiment determined by the sentiment analysis model. The operation may be the transfer of the chat conversation from a chatbot to a human agent or the generation of an outbound message by the chatbot. The system receives positive or negative feedback regarding the appropriateness and/or timeliness of the operation. The positive or negative feedback is attributed to the sentiment analysis model. The system generates training data using the feedback. The system then retrains the sentiment analysis model based on the training data.

Abstract: A system analyzes a set of static source code to identify source code segments that may be implemented using parallel multi-thread processing at run-time. The system determines whether source code segments meet multi-threading criteria, including lacking operational data dependencies and having particular run time or computing resource consumption characteristics. Based on determining that the source code meets multi-threading criteria, the system modifies the static source code to utilize parallel multi-thread processing at run-time. The system generates a recommendation for a user based on the source code modification.

Abstract: Techniques for triggering a transfer of a chat conversation with a user from a chatbot to a human agent based on detection of transfer criteria are disclosed. The chatbot uses natural language processing and a generative model to collect and organize information from the chat conversation to present to the human agent in a report when the chat conversation is transferred to the human agent. The chat conversation is transferred to the human agent by presenting the report and a graphical chat interface to the human agent. The graphical chat interface displays messages from chat conversation between the human agent and the user and displays messages from chat conversations between the human agent and multiple other users. Transferring the chat conversation from the chatbot to the human agent includes presenting interface elements to the human agent for receiving user input from the human agent for transmission to the user.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Abstract: Techniques for triggering a transfer of a chat conversation with a user from a chatbot to a human agent based on detection of transfer criteria are disclosed. The chatbot uses natural language processing and a generative model to collect and organize information from the chat conversation to present to the human agent in a report when the chat conversation is transferred to the human agent. The chat conversation is transferred to the human agent by presenting the report and a graphical chat interface to the human agent. The graphical chat interface displays messages from chat conversation between the human agent and the user and displays messages from chat conversations between the human agent and multiple other users. Transferring the chat conversation from the chatbot to the human agent includes presenting interface elements to the human agent for receiving user input from the human agent for transmission to the user.

Abstract: Layouts for elements of a flowchart or flow diagram may use recursive algorithms that trace along each parent-child pathway to ensure that child elements always occur after parent elements in a horizontal spacing. Vertical spacing requirements may then be calculated for each element, along with a vertical space above a center line and a vertical space below a center line for each element. These vertical spacing requirements may then be used by a recursive algorithm to assign vertical positions to each of the elements. The vertical spacing may ensure that lanes created for each branch element are not crossed by later elements in the process flow, which ensures that connections between elements may be clearly distinguished from each other.

Abstract: Techniques for configuring autosave triggers in a computing environment based on environment and data conditions are disclosed. A system trains a machine learning model based on data attributes and environmental attributes to generate autosave value triggers for a computing environment. The autosave value triggers are triggered by different conditions. For example, one autosave trigger may be triggered when an error condition is detected. Another may be triggered when a certain number of operations are performed. The machine learning model generates autosave trigger values scores for one or more autosave triggers. The system may implement the autosave triggers in the computing environment based on the autosave trigger values.

Abstract: Techniques for drilling back to an original audio clip in virtual assistant initiated lists and reminders are disclosed. The system may receive audio input comprising a first request. Based on the first request, the system may schedule an action to be performed by the virtual assistant platform. The system stores at least a portion of the audio input and a mapping between the action and at least the portion of the audio input. The system performs the action. Subsequent to performing the action, the system receives a second request for audio playback of the first request corresponding to the action. The system retrieves at least the portion of the audio input based on the mapping between the action and at least the portion of the audio input, and plays at least the portion of the audio input comprising the first request.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: Techniques for UNDO and REDO operations in a computer-user interface are disclosed. The techniques enables users to configure entities for UNDO and REDO operations. The techniques also enable users to roll back individual entity to an immediate previous state in one UNDO operation and subsequently to the other previous states. Other entities are not affected by the UNDO operations to the entity.

Abstract: A system drills back to an original audio clip in lists and reminders initiated by a virtual assistant. The system may receive audio input comprising a first request. Based on the first request, the system may schedule an action to be performed by the virtual assistant platform. The system stores at least a portion of the audio input and a mapping between the action and at least the portion of the audio input. The system performs the action. Subsequent to performing the action, the system receives a second request for audio playback of the first request corresponding to the action. The system retrieves at least the portion of the audio input based on the mapping between the action and at least the portion of the audio input, and plays at least the portion of the audio input comprising the first request.