Abstract: A method for friction reduction during professional network expansion is implemented via a computing system including a processor. The method includes executing, via a network, an enterprise application on a remote computing system operated by a user associated with an enterprise and surfacing a professional networking UI on a display of the remote computing system during execution of the enterprise application. The method includes generating parameters that are representative of a connection between the user and each suggested professional contact based on enterprise-level data corresponding to the user and each suggested professional contact and generating friction-reducing UI elements for each suggested professional contact based on the generated parameters.

Abstract: A system and method for managing one or more physical spaces includes receiving data relating to location of a plurality of users, determining based on the location, an occupancy rate of the plurality of users for at least one of the one or more physical spaces, identifying based on the occupancy rate and features provided at the one or more physical spaces, one or more user preferred features, providing the occupancy rate and the user preferred features to a trained machine-learning (ML) model for determining optimal uses for the one or more physical spaces in a future time period, receiving as an output from the trained ML model suggested plans for use or management of the one or more physical spaces in the future time period, and providing the suggested plans for display in a user interface (UI) screen.

Abstract: A method for integrated professional network expansion during employee onboarding is implemented via a computing system including a processor. The method includes executing, via a network, an enterprise application on a first remote computing system operated by an employer associated with an enterprise, as well as causing surfacing of a professional networking UI on a display of the first remote computing system during the execution of the enterprise application. The method also includes receiving, via the professional networking UI surfaced on the display of the first remote computing system, user input including a specification of onboarding parameters for an employee of the enterprise, where the onboarding parameters correspond to one or more professional networking intentions for the employee. The method further includes causing the enterprise application to be executed on a second remote computing system operated by the employee in accordance with the specified onboarding parameters.

Abstract: A method for data-driven professional network expansion techniques is implemented via a computing system including a processor. The method includes executing, via a network, an enterprise application on a remote computing system operated by a user associated with an enterprise and surfacing a professional networking UI on a display of the remote computing system during execution of the enterprise application. The method includes accessing enterprise-level data corresponding to the user and the enterprise, extracting parameters associated with the user and the enterprise from the enterprise-level data, and automatically generating, based on the extracted parameters, the user's professional network and a list of suggested professional contacts.

Abstract: A method for friction reduction during professional network expansion is implemented via a computing system including a processor. The method includes executing, via a network, an enterprise application on a remote computing system operated by a user associated with an enterprise and surfacing a professional networking UI on a display of the remote computing system during execution of the enterprise application. The method includes generating parameters that are representative of a connection between the user and each suggested professional contact based on enterprise-level data corresponding to the user and each suggested professional contact and generating friction-reducing UI elements for each suggested professional contact based on the generated parameters.

Abstract: A system and method for managing one or more physical spaces includes receiving data relating to location of a plurality of users, determining based on the location, an occupancy rate of the plurality of users for at least one of the one or more physical spaces, identifying based on the occupancy rate and features provided at the one or more physical spaces, one or more user preferred features, providing the occupancy rate and the user preferred features to a trained machine-learning (ML) model for determining optimal uses for the one or more physical spaces in a future time period, receiving as an output from the trained ML model suggested plans for use or management of the one or more physical spaces in the future time period, and providing the suggested plans for display in a user interface (UI) screen.

Abstract: A system and method for facilitating convergence includes receiving a request to schedule a meeting at a meeting time, retrieve at least one of user data, contextual data, facility data and map data, the user data including a list of a plurality of meeting participants for the meeting, providing at least one of the list of the plurality of meeting participants, the meeting time, the user data, and the facility data to a trained machine-learning (ML) model for predicting a location at which two or more of the plurality of meeting participants will be located within a given time period prior to the meeting time, receiving the predicted location as an output from the trained ML model, and identifying a meeting location from among one or more meeting venues based on the predicted location of the two or more of the plurality of meeting participants, and providing the meeting location for display in a first selectable user interface element.

Abstract: A system and method for facilitating convergence includes receiving data relating to a first user's history of connections with other users, receiving contextual data about the first user, the contextual data including organizational graph data, providing the data and the contextual data as inputs to a trained machine-learning (ML) model for identifying a second user for the first user to connect with based on the data and the contextual data, receiving the identified second user as an output from the trained ML model, and providing the identified second user as a connection suggestion for display in a user interface element.

Abstract: A calendar application server, a computer-readable storage medium, and corresponding methods for third-party resource management within the context of a calendar application are described herein. The computer-readable storage medium includes computer-executable instructions that, when executed one or more processors, cause the processor(s) to associate a third-party resource with an event within a calendar application in response to a user command received via an event UI functionality provided by the calendar application, to connect with the third-party resource via an API corresponding to the third-party resource in response to another user command received via the event UI functionality (where the API is provided within the context of the calendar application), to generate third-party resource data for the event in response to user interaction with the third-party resource via the API, and to reconcile the third-party resource data with event data within the calendar application.

Abstract: A calendar application server, a computer-readable storage medium, and a corresponding method for food service management for food-associated events within the context of a calendar application are described herein.

Abstract: A system identifies a significant communication from a revived contact. A user and the contact interact, and the interaction is monitored to determine a weighted significance value to attribute to the contact. The interaction may include communication, a designation of significance by the user, and organizational associations. The weighted significance value is attributed to the contact. A subsequent communication is detected and a weighted time difference value for the subsequent communication is determined. If the subsequent communication satisfies a significant communication condition, then the subsequent communication is designated as a significant communication.

Abstract: Non-limiting examples of the present disclosure describe surfacing a representation of digital artifacts for a user. An operation context associated with a user is identified. The operational context may correspond with an electronic document that is accessed through a productivity application. One or more of a plurality of digital artifacts may be identified based on the identified operational context. An exemplary representation of the one or more digital artifacts is surfaced through a user interface. An exemplary user interface may be a user interface of a productivity application, for example, where the electronic document is being accessed through the productivity application. In alternative examples, an exemplary user interface may be associated with a home service that is executed in association with an operating system (OS). In some instances, an operational context may change resulting in an update to an exemplary representation of digital artifacts. Other examples are also described.

Abstract: A system identifies a significant communication from a revived contact. A user and the contact interact, and the interaction is monitored to determine a weighted significance value to attribute to the contact. The interaction may include communication, a designation of significance by the user, and organizational associations. The weighted significance value is attributed to the contact. A subsequent communication is detected and a weighted time difference value for the subsequent communication is determined. If the subsequent communication satisfies a significant communication condition, then the subsequent communication is designated as a significant communication.

Abstract: A system identifies a significant communication from a revived contact. A user and the contact interact, and the interaction is monitored to determine a weighted significance value to attribute to the contact. The interaction may include communication, a designation of significance by the user, and organizational associations. The weighted significance value is attributed to the contact. A subsequent communication is detected and a weighted time difference value for the subsequent communication is determined. If the subsequent communication satisfies a significant communication condition, then the subsequent communication is designated as a significant communication.

Abstract: A system identifies a significant communication from a revived contact. A user and the contact interact, and the interaction is monitored to determine a weighted significance value to attribute to the contact. The interaction may include communication, a designation of significance by the user, and organizational associations. The weighted significance value is attributed to the contact. A subsequent communication is detected and a weighted time difference value for the subsequent communication is determined. If the subsequent communication satisfies a significant communication condition, then the subsequent communication is designated as a significant communication.

Abstract: Non-limiting examples of the present disclosure describe surfacing a representation of digital artifacts for a user. An operation context associated with a user is identified. The operational context may correspond with an electronic document that is accessed through a productivity application. One or more of a plurality of digital artifacts may be identified based on the identified operational context. An exemplary representation of the one or more digital artifacts is surfaced through a user interface. An exemplary user interface may be a user interface of a productivity application, for example, where the electronic document is being accessed through the productivity application. In alternative examples, an exemplary user interface may be associated with a home service that is executed in association with an operating system (OS). In some instances, an operational context may change resulting in an update to an exemplary representation of digital artifacts. Other examples are also described.