公开(公告)号：US20230030228A1

公开(公告)日：2023-02-02

申请号：US17934001

申请日：2022-09-21

申请人： NASDAQ, INC.

发明人： Xuyang LIN ,  Tudor MOROSAN ,  Douglas HAMILTON ,  Shihui CHEN ,  Hyunsoo JEONG ,  Jonathan RIVERS ,  Leonid ROSENFELD

IPC分类号： G06F16/23 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

摘要： A computer system is provided for monitoring and detecting changes in a data generating processes, which may be under a multi-dimensional and unsupervised setting. A target dataset is split into paired subgroups by a separator and one or more detectors are applied to detect changes, anomalies, inconsistencies, and the like between the paired subgroups. Metrics may be generated by the detector(s), which are then passed to an evaluating system.

公开(公告)号：US20220245116A1

公开(公告)日：2022-08-04

申请号：US17727886

申请日：2022-04-25

申请人： Nasdaq, Inc.

发明人： Jonathan RIVERS ,  Douglas HAMILTON ,  Leonid ROSENFELD

IPC分类号： G06F16/22 ,  G06N3/08 ,  G06F16/248 ,  G06F16/28

摘要： The described technology relates to systems and techniques for accessing a database by dynamically choosing an index from a plurality of indexes that includes at least one learned index and at least one non-learned index. The availability of learned and non-learned indexes for accessing the same database provides for flexibility in accessing the database, and the dynamic selection between learned indexes and non-learned indexes provide for choosing the index based on the underlying data in the database and the characteristics of the query. Certain example embodiments provide a learned model that accepts a set of features associated with the query as input, and outputs a set of evaluated weights for respective features, which are then processed according to a set of rules to predict the most efficient index to be used.

公开(公告)号：US20240004862A1

公开(公告)日：2024-01-04

申请号：US18469273

申请日：2023-09-18

申请人： NASDAQ, INC.

发明人： Xuyang LIN ,  Tudor MOROSAN ,  Douglas HAMILTON ,  Shihui CHEN ,  Hyunsoo JEONG ,  Jonathan RIVERS ,  Leonid ROSENFELD

IPC分类号： G06F16/23 ,  G06N3/088 ,  G06F18/214 ,  G06N3/045

CPC分类号： G06F16/2358 ,  G06N3/088 ,  G06F18/2155 ,  G06N3/045

摘要： A computer system is provided for monitoring and detecting changes in a data generating processes, which may be under a multi-dimensional and unsupervised setting. A target dataset is split into paired subgroups by a separator and one or more detectors are applied to detect changes, anomalies, inconsistencies, and the like between the paired subgroups. Metrics may be generated by the detector(s), which are then passed to an evaluating system.

公开(公告)号：US20230350866A1

公开(公告)日：2023-11-02

申请号：US18218278

申请日：2023-07-05

申请人： Nasdaq, Inc.

发明人： Jonathan RIVERS ,  Douglas HAMILTON ,  Leonid ROSENFELD

IPC分类号： G06F16/22 ,  G06F16/28 ,  G06N3/08 ,  G06F16/248

CPC分类号： G06F16/2272 ,  G06F16/248 ,  G06F16/285 ,  G06N3/08

摘要： The described technology relates to systems and techniques for accessing a database by dynamically choosing an index from a plurality of indexes that includes at least one learned index and at least one non-learned index. The availability of learned and non-learned indexes for accessing the same database provides for flexibility in accessing the database, and the dynamic selection between learned indexes and non-learned indexes provide for choosing the index based on the underlying data in the database and the characteristics of the query. Certain example embodiments provide a learned model that accepts a set of features associated with the query as input, and outputs a set of evaluated weights for respective features, which are then processed according to a set of rules to predict the most efficient index to be used.