公开(公告)号：US20220006823A1

公开(公告)日：2022-01-06

申请号：US16918033

申请日：2020-07-01

Applicant: VMware, Inc.

Inventor： Kar-Fai Tse ,  Chaoting Xuan ,  Ravish Chawla ,  Erich Stuntebeck ,  Stephen Jonathan Parry-Barwick

IPC: H04L29/06 ,  H04L12/24

Abstract: Disclosed are various approaches for automating the detection and identification of anomalous devices in a management service. Device check-ins are received by a management service and housed in a data store. The quantity of device check-ins over various time periods can be analyzed using various approaches to identify anomalous devices.

公开(公告)号：US20230396660A1

公开(公告)日：2023-12-07

申请号：US17830733

申请日：2022-06-02

Applicant: VMware, Inc.

Inventor： Rohit Pradeep Shetty ,  Ravish Chawla ,  Adam Chow

IPC: H04L65/403 ,  H04L65/1083 ,  H04L41/12 ,  G06Q10/10 ,  H04L43/0811

CPC classification number: H04L65/403 ,  H04L65/1083 ,  H04L41/12 ,  G06Q10/1095 ,  H04L43/0811

Abstract: Systems and methods are described for providing recommendations for an improved user experience in online meetings. A recommendation engine can aggregate data from user devices to make recommendations before, during and after online meetings. Before a meeting, the recommendation engine can recommend which of a user's devices to use for the meeting. During the meeting, the recommendation engine can identify current or anticipated issues and recommend changes the user can make to correct or prevent the issue. After meetings, the recommendation engine can aggregate data and identify an ongoing issue for one or multiple users. The recommendation engine can identify the cause of the issue and make recommendations to the user or an administrator accordingly.

公开(公告)号：US20230396487A1

公开(公告)日：2023-12-07

申请号：US17830762

申请日：2022-06-02

Applicant: VMware, Inc.

Inventor： Rohit Pradeep Shetty ,  Ravish Chawla ,  Adam Chow

IPC: H04L41/0668 ,  H04L41/12 ,  H04L41/16 ,  H04L41/5074 ,  H04L41/0631

CPC classification number: H04L41/0668 ,  H04L41/12 ,  H04L41/16 ,  H04L41/5074 ,  H04L41/0631

Abstract: Systems and methods are described for providing recommendations for an improved user experience in online meetings. A recommendation engine can aggregate data from user devices to make recommendations before, during and after online meetings. Before a meeting, the recommendation engine can recommend which of a user's devices to use for the meeting. During the meeting, the recommendation engine can identify current or anticipated issues and recommend changes the user can make to correct or prevent the issue. After meetings, the recommendation engine can aggregate data and identify an ongoing issue for one or multiple users. The recommendation engine can identify the cause of the issue and make recommendations to the user or an administrator accordingly.

公开(公告)号：US11182214B2

公开(公告)日：2021-11-23

申请号：US16451632

申请日：2019-06-25

Applicant: VMware, Inc.

Inventor： Erich Peter Stuntebeck ,  Ravish Chawla ,  Kar Fai Tse

IPC: G06F9/50 ,  G06N20/00 ,  G06K19/00 ,  G06F9/455 ,  G06K19/07

Abstract: Various examples are disclosed for predictive allocation of computing resources based on the predicted location of a user. A computing environment can generate a predictive usage model that predicts a location of a user and allocate computing resources, such as VDI sessions or VMs, to a host device that optimizes latency to the predicted location.

公开(公告)号：US20210027155A1

公开(公告)日：2021-01-28

申请号：US16519338

申请日：2019-07-23

Applicant: VMware, Inc.

Inventor： Ravish Chawla ,  Kar-Fai Tse ,  Chaoting Xuan

IPC: G06N3/08 ,  G06F17/21 ,  G06F9/38 ,  G06Q10/10

Abstract: Examples described herein include systems and methods for implementing customized, on-device processing workflows. An example method can include training different natural language processing (“NLP”) models using distinct datasets relevant to different backend systems. The different NLP models can be assigned to user devices based on each device user's organizational group. The user devices can implement the customized NLP models to detect triggers within text of an application. Based on the detected trigger, the application can display a user interface element having a selectable actionable button for carrying out an action with respect to the backend system. In some examples, the detected trigger can automatically cause an action to be carried out with respect to the backend system.