公开(公告)号：US20140280239A1

公开(公告)日：2014-09-18

申请号：US13962103

申请日：2013-08-08

Applicant: SAS Institute Inc.

Inventor： James Edward Georges ,  David Lee Kuhn ,  Edward Lew Rowe ,  John Michael Kichak ,  Karcsi Fritz Lehr

IPC: G06F17/30

CPC classification number: G06F16/2468 ,  G06F21/6254

Abstract: A method of determining a similarity between records in a data set is provided. Data organized into a plurality of records is received. First characters associated with a field and a first record of the plurality of records are selected. The selected first characters are subdivided into a first sliding series of a defined number of characters. Second characters associated with the field and a second record of the plurality of records are selected. The selected second characters are subdivided into a second sliding series of the defined number of characters. A similarity score between the first sliding series and the second sliding series is calculated. Whether or not the first sliding series and the second sliding series are similar is determined based on the calculated similarity score.

Abstract translation: 提供了一种确定数据集中的记录之间的相似性的方法。 接收组织成多个记录的数据。 选择与多个记录的字段和第一记录相关联的第一个字符。 所选择的第一个字符被细分为一个定义数量的字符的第一个滑动系列。 选择与字段相关联的第二字符和多个记录的第二记录。 所选择的第二个字符被细分为定义数量的字符的第二个滑动系列。 计算第一滑动系列和第二滑动系列之间的相似性得分。 基于所计算出的相似性得分确定第一滑动系列和第二滑动系列是否相似。

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：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：US20140280343A1

公开(公告)日：2014-09-18

申请号：US14016689

申请日：2013-09-03

Applicant: SAS Institute Inc.

Inventor： James Edward Georges ,  David Lee Kuhn ,  Edward Lew Rowe ,  John Michael Kichak ,  Karcsi Fritz Lehr

IPC: G06F17/30

CPC classification number: G06F16/2468 ,  G06F21/6254

Abstract: A method of determining a similarity between records in a data set is provided. Data organized into a plurality of records is received. First characters associated with a field and a first record of the plurality of records are selected. The selected first characters are encoded and subdivided into a first sliding series of a defined number of characters. Second characters associated with the field and a second record of the plurality of records are selected. The selected second characters are encoded and subdivided into a second sliding series of the defined number of characters. Whether or not the first sliding series and the second sliding series are similar is determined by comparing the encoded and subdivided first characters to the encoded and subdivided second characters using a fuzzy matching algorithm.

Abstract translation: 提供了一种确定数据集中的记录之间的相似性的方法。 接收组织成多个记录的数据。 选择与多个记录的字段和第一记录相关联的第一个字符。 所选择的第一个字符被编码并被细分成一个定义数量的字符的第一个滑动系列。 选择与字段相关联的第二字符和多个记录的第二记录。 所选择的第二个字符被编码并细分为定义数量的字符的第二个滑动系列。 通过使用模糊匹配算法将编码和细分的第一字符与编码和细分的第二字符进行比较来确定第一滑动系列和第二滑动系列是否相似。

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.