Abstract: A computer-implemented method can receive a message sent from a source entity, perform first pre-processing operations for verifying validity of the message, perform second pre-processing operations for determining a category of the message, extract metadata from the message, generate an enriched message comprising the metadata and the determined category, perform post-processing operations for classifying the enriched message into one of a plurality of event types, broadcast the enriched message to a message broker, and routing, by the message broker, the enriched message to one or more target entities registered an event type into which the message is classified.

Abstract: Embodiments of the present disclosure include techniques for controlling access to electronic content. In one embodiment, a user generates content in an electronic document. The system retrieves the content and a profile for the user. A predictive engine determines an access control list comprising a plurality of entries based on the content and the profile. The access control list may be presented to the user, and the system receives a verification from the user of the plurality of entries in the access control list.

Abstract: A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.

Abstract: A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.

Abstract: Techniques and solutions are provided for facilitating the definition and use of virtual environments. Typically, virtual environments require manual linking of virtual environment components, such as locations, avatars to be displayed, avatar interactions, and actions to be taken upon a selected interaction. This is in addition to actions to define, for example, a visual representation of a virtual location or an avatar. Disclosed techniques provide standardized data objects that can represent components of a virtual environment and relationships between such components. For example, aspects of a virtual environment can be predefined, and a user can configure the virtual environment with particular avatars and particular avatar content (such as media to be rendered for that avatar). In particular aspects, components of a virtual environment, such as avatars, can be determined at runtime, included based on attributes associated with a particular user for whom the virtual environment is to be rendered.

Abstract: A computer-implemented method can instantiate a net graph based on one or more existing bills of materials for one or more known entities. The net graph includes a plurality of interconnected nodes representing different objects included in the one or more known entities, and the one or more existing bill of materials define relationship between the objects. The method can determine carbon footprint values of the objects represented by the nodes, collect vectors of object features and carbon footprint values corresponding to selected nodes in the net graph, train a machine learning model using the collected vectors of object features and the carbon footprint values corresponding to the selected nodes, receiving a request associated with a target entity different from the one or more known entities, and responsive to the request, generate an estimated carbon footprint value for the target entity based on the machine learning model.

Abstract: A computer-implemented method can receive a message sent from a source entity, perform first pre-processing operations for verifying validity of the message, perform second pre-processing operations for determining a category of the message, extract metadata from the message, generate an enriched message comprising the metadata and the determined category, perform post-processing operations for classifying the enriched message into one of a plurality of event types, broadcast the enriched message to a message broker, and routing, by the message broker, the enriched message to one or more target entities registered an event type into which the message is classified.

Abstract: Technologies and solutions are provided for improving process efficiency/identifying efficient paths of process steps. A target outcome can be identified, which can be a particular status, such as a stage (or status/step) in a process, or a target outcome can be an identification of particular process statuses that can be reached, such as given a particular set of constraints. Proceeding between process steps involves the use of resources, where a process step can be reached, or having an increased chance of being reached, when the resources have been obtained. Various paths can exist for obtaining a resource, where some paths can be more efficient than others. Based on resource paths and paths between steps of a process, one or more paths can be suggested for reaching the target outcome, including providing information about the process step paths or the resources paths for reaching the target outcome.

Abstract: A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.

Abstract: A method includes receiving a message query from an entity identifier participating in a social network. The message query specifies one or more entities, one or more requirements, and one or more constraints. A set of message query parameters is generated based on the message query. A set of queries for a semantic graph of the social network is generated based on the set of message query parameters. The set of queries is applied to the semantic graph to obtain a set of query results. A message context of the entity identifier is determined based on the set of query results and the set of message query parameters. A set of messages from a message repository is determined based on the message context. The set of messages can be presented on a client computer associated with the entity identifier.

Abstract: Systems, methods, and computer media for determining compatible users through machine learning are provided herein. Previous interactions between some users in a group can be used to determine a first set of user-to-user compatibility scores. Both the first set of compatibility scores and attributes for the users in the group can be provided as inputs to a machine learning model that can be used to determine a second set of user-to-user compatibility scores for user pairs who do not have an interaction history. Along with input constraints, the first and second sets of user-to-user compatibility scores can be used to select compatible user groups.

Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.

Abstract: A method, a system, and a computer program product for accessing data. A data stream including a plurality of data elements is received. A mapping of the plurality of data elements is generated. Each data element is represented by a data node in the mapping. A linked list of the data nodes with starting and ending elements is generated. Each node is linked to at least another node and stores a count of a data element and the corresponding data element. The count represents a number of times the data element is present in the data stream. Each node is positioned in the generated linked list using the count of each data element. Data elements with a highest count are positioned proximate to the starting element and data elements with a lowest count are positioned proximate to the ending element. Data elements are accessed using the generated mapping.

Abstract: A method may include training one or more machine learning models to predict a decline in employee performance. The machine learning models may be trained in a federated manner to avoid the exchange of personal data. The trained machine learning models may be applied to data associated with an employee that corresponds to one or more leading indicators of employee burnout. In response to the trained machine learning models predicting a decline in the performance of the employee, the root causes of the predicted decline in the performance of the employee may be identified by applying an explainability algorithm such as Shapley Additive Explanations (SHAP). A report including a corrective action for the predicted decline in employee performance may be generated based on the root causes. Related systems and computer program products are also provided.

Abstract: A method, a system, and a computer program product for accessing data. A data stream including a plurality of data elements is received. A mapping of the plurality of data elements is generated. Each data element is represented by a data node in the mapping. A linked list of the data nodes with starting and ending elements is generated. Each node is linked to at least another node and stores a count of a data element and the corresponding data element. The count represents a number of times the data element is present in the data stream. Each node is positioned in the generated linked list using the count of each data element. Data elements with a highest count are positioned proximate to the starting element and data elements with a lowest count are positioned proximate to the ending element. Data elements are accessed using the generated mapping.

Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.

Abstract: A method, a system, and a computer program product for accessing data. A data stream including a plurality of data elements is received. A mapping of the plurality of data elements is generated. Each data element is represented by a data node in the mapping. A linked list of the data nodes with starting and ending elements is generated. Each node is linked to at least another node and stores a count of a data element and the corresponding data element. The count represents a number of times the data element is present in the data stream. Each node is positioned in the generated linked list using the count of each data element. Data elements with a highest count are positioned proximate to the starting element and data elements with a lowest count are positioned proximate to the ending element. Data elements are accessed using the generated mapping.