Contextual disambiguation of an entity in a conversation management system

    公开(公告)号:US11205048B2

    公开(公告)日:2021-12-21

    申请号:US16444801

    申请日:2019-06-18

    摘要: Systems, computer-implemented methods, and computer program products that can facilitate word entity disambiguation are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a language model component that employs an artificial intelligence model to generate a profile vector of an entity based on one or more binary values representing profile data of the entity and a word vector of a word entity in a dialogue based on one or more second word entities adjacent to the word entity in the dialogue. The computer executable components can further comprise a dialogue management component that disambiguates the word entity based on the profile vector and the word vector.

    Meeting room reservation system
    2.
    发明授权

    公开(公告)号:US11188878B2

    公开(公告)日:2021-11-30

    申请号:US14861959

    申请日:2015-09-22

    IPC分类号: G06Q10/10

    摘要: Embodiments of the present invention provide a method comprising maintaining historical meeting information, receiving an event data stream corresponding to a meeting, and delaying confirmation of an assignment of a meeting room for the meeting for a period of delay defined by a confirmation condition to predict a number of in-person attendees at the meeting based on the event data stream and the historical meeting information. The meeting room is tentatively assigned to the meeting based on the predicted number of in-person attendees. The method further comprises sending confirmation of the assignment of the meeting room for the meeting to at least one invitee only after the period of delay has elapsed.

    Missing value imputation using adaptive ordering and clustering analysis

    公开(公告)号:US11010365B2

    公开(公告)日:2021-05-18

    申请号:US15939521

    申请日:2018-03-29

    摘要: As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.

    Drone air traffic control and flight plan management

    公开(公告)号:US10540900B2

    公开(公告)日:2020-01-21

    申请号:US15799826

    申请日:2017-10-31

    IPC分类号: G08G5/00

    摘要: One embodiment provides a method comprising receiving a flight plan request for a drone. The flight plan request comprises a drone identity, departure information, and arrival information. The method further comprises constructing a modified flight plan for the drone based on the flight plan request, wherein the modified flight plan represents an approved, congestion reducing, and executable flight plan for the drone, and the modified flight plan comprises a sequence of four-dimensional (4D) cells representing a planned flight path for the drone. For each 4D cell of the modified flight plan, the method further comprises attempting to place an exclusive lock on behalf of the drone on the 4D cell, and in response to a failure to place the exclusive lock on behalf of the drone on the 4D cell, rerouting the modified flight plan around the 4D cell to a random neighboring 4D cell.

    MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS

    公开(公告)号:US20190303471A1

    公开(公告)日:2019-10-03

    申请号:US15939521

    申请日:2018-03-29

    IPC分类号: G06F17/30

    摘要: As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.

    Estimating file level input/output operations per second (IOPS)

    公开(公告)号:US10032115B2

    公开(公告)日:2018-07-24

    申请号:US15145560

    申请日:2016-05-03

    摘要: A computer-implemented method according to one embodiment includes identifying a storage volume comprising a plurality of files, calculating a file level input/output operations per second (IOPS) value for each of a subset of the plurality of files within the storage volume, creating a predictive model for the storage volume, using metadata determined for the subset of the plurality of files and the IOPS values calculated for each of the subset of the plurality of files within the storage volume, estimating file level IOPS values for each of the plurality of files in the storage volume, utilizing the predictive model, combining the estimated and calculated file level IOPS values and comparing the combined values to a calculated volume level IOPS value for the storage volume, conditionally adjusting one or more of the estimated file level IOPS values, based on the comparing, and returning the estimated file level IOPS values.