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.