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1. 发明授权

US11501205B2 System and method for synthesizing data 有权
公开(公告)号：US11501205B2
公开(公告)日：2022-11-15
申请号：US16536538
申请日：2019-08-09
申请人： Cigna Intellectual Property, Inc.
发明人： David Fogarty , Jing Lin
IPC分类号： G06N5/04 , G06N20/00
摘要： Systems and methods for constructing sets of synthetic data. A single data record is identified from a first set of data. The first set of data comprises a first plurality of data records, each of the data records including multiple items of data describing an entity. Using pattern recognition, the single data record is processed to identify a group of records from within the first set that have corresponding characteristics equivalent to the single data record. The identified group of records comprises a target set of variables and the group of records from the first set that are not identified comprises a control set of variables. The target set of variables and the control set of variables are processed, using probability estimation and optimization constraints, to determine a score for each of the records in the first set. The score describes how similar each of the records in the first set is to the single data record. The records associated with a percentage of the highest scores are identified. The data associated with the single data record is replaced with data associated with the identified records identified, item-by-item.

2. 发明授权

US10423890B1 System and method for synthesizing data 有权
公开(公告)号：US10423890B1
公开(公告)日：2019-09-24
申请号：US14567432
申请日：2014-12-11
申请人： CIGNA Intellectual Property, Inc.
发明人： David Fogarty , Jing Lin
IPC分类号： G06N20/00 , G06N5/04
摘要： A single data record is identified from a first set of data. The first set of data comprises a first plurality of data records, each of the data records including multiple items of data describing an entity. Using pattern recognition, the single data record is processed to identify a group of records from within the first set that have corresponding characteristics equivalent to the single data record. A score for each of the records in the first set is determined. The score describes how similar each of the records in the first set is to the single data record.

3. 发明申请

US20230052823A1 SYSTEM AND METHOD FOR SYNTHESIZING DATA 有权
公开(公告)号：US20230052823A1
公开(公告)日：2023-02-16
申请号：US17967147
申请日：2022-10-17
申请人： Cigna Intellectual Property, Inc.
发明人： David J. Fogarty , Jing Lin
IPC分类号： G06N20/00 , G06N5/04
摘要： Systems and methods for constructing sets of synthetic data. A single data record is identified from a first set of data. The first set of data comprises a first plurality of data records, each of the data records including multiple items of data describing an entity. Using pattern recognition, the single data record is processed to identify a group of records from within the first set that have corresponding characteristics equivalent to the single data record. The identified group of records comprises a target set of variables and the group of records from the first set that are not identified comprises a control set of variables. The target set of variables and the control set of variables are processed, using probability estimation and optimization constraints, to determine a score for each of the records in the first set. The score describes how similar each of the records in the first set is to the single data record. The records associated with a percentage of the highest scores are identified. The data associated with the single data record is replaced with data associated with the identified records identified, item-by-item.

4. 发明授权

US09881031B1 System and method for combining data sets 有权
公开(公告)号：US09881031B1
公开(公告)日：2018-01-30
申请号：US14627198
申请日：2015-02-20
申请人： CIGNA Intellectual Property, Inc.
发明人： Jing Lin , David Fogarty , Chit Ming Yip , Wanyu Liao
IPC分类号： G06F15/18 , G06F17/30 , G06N99/00 , G06N5/04
CPC分类号： G06F17/30289 , G06N5/04 , G06N99/005
摘要： Embodiments of the invention involve receiving a first set of data describing one or more first observations and a second set of data describing one or more second observations. The first set of data comprises at least two types of data and the second set of data comprises at least two types of data. At least one of the two types of data in the first data set are common with at least one of the two types of data in the second data set. The common types of data comprise common data to the first and second sets of data. The types of data that are not common comprise exclusive data for each of the first and second sets of data. A first multiple regression model is developed for the first data set. The common data for the first data set are set as independent variables and the exclusive data for the first data set are set as dependent variables. A second multiple regression model is developed for the second data set. The common data for the second data set are set as independent variables and the exclusive data for the second data set are set as dependent variables. Prediction results of the first and second multiple regression models are received. Based on the prediction results, at least some of the one or more first observations and the one or more second observations are classified as reasonable observations, which are well-predicted observations. At least some of the one or more first observations and the one or more second observations are classified as outlier observations, which are not classified as well-predicted observations. The outlier observations are removed. The reasonable observations are assigned into intervals for each of the types of data. Based on the assignment, the observations are merged to create a third data set.

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