MEETING ATTENDANCE TRACKING SYSTEM
    1.
    发明申请

    公开(公告)号:US20170357947A1

    公开(公告)日:2017-12-14

    申请号:US15180986

    申请日:2016-06-13

    Abstract: Various systems and methods for providing a meeting attendance tracking system are provided herein. A meeting attendance tracking system includes an indoor positioning service coupled to a plurality of radio transmitters, and operable to determine a location of a user device, the user device associated with a user, the location of the user device corresponding with a location of the user; a database interface to: access a database of scheduled events for the user; and determine a current event from the database of scheduled events, the current event corresponding with a current time and date; and a scheduler coupled to the indoor positioning service and the database interface, to: determine that the location of the user device does not correspond with a location of the current event; determine whether the user is attending a conflicting event; and provide a notification to the user or a meeting organizer regarding the current event.

    Contextual model-based event scheduling

    公开(公告)号:US10685332B2

    公开(公告)日:2020-06-16

    申请号:US15191594

    申请日:2016-06-24

    Abstract: Various techniques for performing contextual event scheduling with an event scheduling service are disclosed herein. In an example, data is processed at an event scheduling service, based on the use of a trained machine learning model that is specific to a user. This trained machine learning model is operated by the event scheduling service determine a proposed time and proposed scheduling parameters based on the contextual information, to identify a proposed event time and event scheduling parameters based on the model, the data indicating a user state, or external data. Further examples to evaluate user activity and identify schedule characteristics based on data inputs from a user's mobile computing device, wearable sensors, and external weather, traffic, or event data sources, are also disclosed.

    CONTEXTUAL MODEL-BASED EVENT SCHEDULING
    4.
    发明申请

    公开(公告)号:US20170372268A1

    公开(公告)日:2017-12-28

    申请号:US15191594

    申请日:2016-06-24

    Abstract: Various techniques for performing contextual event scheduling with an event scheduling service are disclosed herein. In an example, data is processed at an event scheduling service, based on the use of a trained machine learning model that is specific to a user. This trained machine learning model is operated by the event scheduling service determine a proposed time and proposed scheduling parameters based on the contextual information, to identify a proposed event time and event scheduling parameters based on the model, the data indicating a user state, or external data. Further examples to evaluate user activity and identify schedule characteristics based on data inputs from a user's mobile computing device, wearable sensors, and external weather, traffic, or event data sources, are also disclosed.

    CONTEXTUAL MODEL-BASED EVENT RESCHEDULING AND REMINDERS

    公开(公告)号:US20170372267A1

    公开(公告)日:2017-12-28

    申请号:US15191591

    申请日:2016-06-24

    CPC classification number: G06Q10/1095

    Abstract: Various techniques for performing contextual event rescheduling with an event scheduling service are disclosed herein. In an example, data is processed at an event scheduling service, based on the use of a trained machine learning model that is specific to a user. This model is operated by the event scheduling service determine a contextual action option for rescheduling an electronic communication event at a proposed time with proposed scheduling parameters. The model may identify the proposed time and event scheduling parameters, from data indicating a user state, or external data, in addition to a semantic text option (such as “Call Back After Meeting”) corresponding to the proposed time and event scheduling parameters. Further examples to evaluate user activity and identify reschedule options based on data inputs from a user's mobile computing device, wearable sensors, and external weather, traffic, or event data sources, are also disclosed.

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