公开(公告)号：US10761894B2

公开(公告)日：2020-09-01

申请号：US16177289

申请日：2018-10-31

Applicant: SAS Institute Inc.

Inventor： Ruth Ellen Baldasaro ,  Jennifer Lee Hargrove ,  Edward Lew Rowe ,  Emily Louise Chapman-McQuiston

IPC: G06F9/50 ,  G06N3/08 ,  G06F16/906 ,  G06F16/9038 ,  G06F16/9035

Abstract: Exemplary embodiments relate to systems for building a model of changes to data items when information the data items is limited or not directly observed. Exemplary embodiments allow properties of the data items to be inferred using a single data structure and creates a highly granular log of changes to the data item. Using this data structure, the time-varying nature of changes to the data item can be determined. The data structure may be used to identify characteristics associated with a regularly-performed action, to examine how adherence to the action affects a system, and to identify outcomes of non-adherence. Fungible data items may be mapped to a remediable condition or remedy class. This may be accomplished by automatically deriving conditions and remedial information from available information, matching the conditions to remedial classes or types via a customizable mapping, and then calculating adherence for the condition on the available information.

公开(公告)号：US12113660B1

公开(公告)日：2024-10-08

申请号：US18581450

申请日：2024-02-20

Applicant: SAS Institute Inc.

Inventor： Jennifer Lee Hargrove ,  Ellen Laura Mir ,  John L. Maynard ,  Karen D. Haralson ,  Corey K. Kozak

IPC: H04L41/06 ,  H04L41/046 ,  H04L41/22

CPC classification number: H04L41/06 ,  H04L41/046 ,  H04L41/22

Abstract: In some examples a system can receive sets of usage data from agent computer systems associated with agents. The agents can be associated with service providers that provide services to service users. The system can generate a corresponding set of metric values for a common set of metrics for each agent based on a corresponding set of usage data. The common set of metrics can be used for all of the agents to detect anomalies related to the agents. The system can generate a score for each agent based on the corresponding set of metric values, wherein the score indicates a risk level associated with the agent. The system can compare the scores for the agents to a predefined threshold to identify one or more agents that may be problematic. The system can then generate a graphical user interface indicating the one or more identified agents.

公开(公告)号：US20190310891A1

公开(公告)日：2019-10-10

申请号：US16177289

申请日：2018-10-31

Applicant: SAS Institute Inc.

Inventor： Ruth Ellen Baldasaro ,  Jennifer Lee Hargrove ,  Edward Lew Rowe ,  Emily Louise Chapman-McQuiston

IPC: G06F9/50 ,  G06N3/08 ,  G06F16/906

Abstract: Exemplary embodiments relate to systems for building a model of changes to data items when information the data items is limited or not directly observed. Exemplary embodiments allow properties of the data items to be inferred using a single data structure and creates a highly granular log of changes to the data item. Using this data structure, the time-varying nature of changes to the data item can be determined. The data structure may be used to identify characteristics associated with a regularly-performed action, to examine how adherence to the action affects a system, and to identify outcomes of non-adherence. Fungible data items may be mapped to a remediable condition or remedy class. This may be accomplished by automatically deriving conditions and remedial information from available information, matching the conditions to remedial classes or types via a customizable mapping, and then calculating adherence for the condition on the available information.

公开(公告)号：US10929193B2

公开(公告)日：2021-02-23

申请号：US16531506

申请日：2019-08-05

Applicant: SAS Institute Inc.

Inventor： Ruth Ellen Baldasaro ,  Jennifer Lee Hargrove ,  Edward Lew Rowe ,  Emily Louise Chapman-McQuiston

IPC: G06N3/08 ,  G06F9/50 ,  G06F16/906 ,  G06F16/9038 ,  G06F16/9035

Abstract: Exemplary embodiments relate to systems for building a model of changes to data items when information the data items is limited or not directly observed. Exemplary embodiments allow properties of the data items to be inferred using a single data structure and creates a highly granular log of changes to the data item. Using this data structure, the time-varying nature of changes to the data item can be determined. The data structure may be used to identify characteristics associated with a regularly-performed action, to examine how adherence to the action affects a system, and to identify outcomes of non-adherence. Fungible data items may be mapped to a remediable condition or remedy class. This may be accomplished by automatically deriving conditions and remedial information from available information, matching the conditions to remedial classes or types via a customizable mapping, and then calculating adherence for the condition on the available information.

公开(公告)号：US20190354410A1

公开(公告)日：2019-11-21

申请号：US16531506

申请日：2019-08-05

Applicant: SAS Institute Inc.

Inventor： Ruth Ellen Baldasaro ,  Jennifer Lee Hargrove ,  Edward Lew Rowe ,  Emily Louise Chapman-McQuiston

IPC: G06F9/50 ,  G06F16/906 ,  G06N3/08

Abstract: Exemplary embodiments relate to systems for building a model of changes to data items when information the data items is limited or not directly observed. Exemplary embodiments allow properties of the data items to be inferred using a single data structure and creates a highly granular log of changes to the data item. Using this data structure, the time-varying nature of changes to the data item can be determined. The data structure may be used to identify characteristics associated with a regularly-performed action, to examine how adherence to the action affects a system, and to identify outcomes of non-adherence. Fungible data items may be mapped to a remediable condition or remedy class. This may be accomplished by automatically deriving conditions and remedial information from available information, matching the conditions to remedial classes or types via a customizable mapping, and then calculating adherence for the condition on the available information.