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公开(公告)号:US11720579B2
公开(公告)日:2023-08-08
申请号:US17367882
申请日:2021-07-06
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Paul O'Hara , Malte Christian Kaufmann , Alan McShane , Anirban Banerjee , Mark Ahern
IPC: G06F16/2458 , G06F16/28 , G06F16/2457
CPC classification number: G06F16/2462 , G06F16/2457 , G06F16/283
Abstract: Systems and methods include determination, for each of a plurality of discrete features, of statistics based on a number of occurrences of each discrete value of the discrete feature in the data, determination of first summary statistics based on the determined statistics, determine of a dissimilarity for each discrete feature based on the first summary statistics and on the statistics determined for the discrete feature, determination of candidate discrete features based on the determined dissimilarities, determination, for each of the candidate discrete features, of second summary statistics based on values of a continuous feature associated with each discrete value of the candidate discrete feature, determination of a deviation score for each of the candidate discrete features based on the second summary statistics, and transmission of the candidate discrete features for display in association with the continuous feature based on the determined deviation scores.
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公开(公告)号:US10305967B2
公开(公告)日:2019-05-28
申请号:US15261194
申请日:2016-09-09
Applicant: Business Objects Software Ltd.
Inventor: Jacques Doan Huu , Alan McShane , Ahmed Abdelrahman , Fadi Maali , Milena Caires
IPC: H04L29/08 , H04L29/06 , G06F9/50 , G06F9/54 , G06F16/182
Abstract: Techniques are described for providing a unified client to interact with a distributed processing platform such as a Hadoop cluster. The unified client may include multiple sub-clients each of which is configured to interface with a particular subsystem of the distributed processing platform, such as MapReduce, Hive, Spark, and so forth. The unified client may be included in an application to provide, for the application, a single interface for communications between the application and the distributed processing platform during a unified communication session.
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公开(公告)号:US20200004891A1
公开(公告)日:2020-01-02
申请号:US16134043
申请日:2018-09-18
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Apoorva Kumar , Alan McShane
IPC: G06F17/30 , G06F15/18 , G06F3/0486
Abstract: Techniques are described for integrating prediction capabilities from data management platforms into applications. Implementations employ a data science platform (DSP) that operates in conjunction with a data management solution (e.g., a data hub). The DSP can be used to orchestrate data pipelines using various machine learning (ML) algorithms and/or data preparation functions. The data hub can also provide various orchestration and data pipelining capabilities to receive and handle data from various types of data sources, such as databases, data warehouses, other data storage solutions, internet-of-things (IoT) platforms, social networks, and/or other data sources. In some examples, users such as data engineers and/or others may use the implementations described herein to handle the orchestration of data into a data management platform.
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公开(公告)号:US20170264670A1
公开(公告)日:2017-09-14
申请号:US15261194
申请日:2016-09-09
Applicant: Business Objects Software Ltd.
Inventor: Jacques Doan Huu , Alan McShane , Ahmed Abdelrahman , Fadi Maali , Milena Caires
CPC classification number: H04L67/10 , G06F9/5072 , G06F9/54 , G06F9/541 , G06F9/547 , G06F17/30194 , H04L67/141 , H04L67/42 , Y02D10/22 , Y02D10/36
Abstract: Techniques are described for providing a unified client to interact with a distributed processing platform such as a Hadoop cluster. The unified client may include multiple sub-clients each of which is configured to interface with a particular subsystem of the distributed processing platform, such as MapReduce, Hive, Spark, and so forth. The unified client may be included in an application to provide, for the application, a single interface for communications between the application and the distributed processing platform during a unified communication session.
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公开(公告)号:US20170262769A1
公开(公告)日:2017-09-14
申请号:US15261215
申请日:2016-09-09
Applicant: Business Objects Software Ltd.
Inventor: Alan McShane , Jacques Doan Huu , Ahmed Abdelrahman , Antoine Carme , Bertrand Lamy , Fadi Maali , Laya Ouologuem , Milena Caires , Nicolas Dulian , Erik Marcade
CPC classification number: G06N20/00 , G06F9/5027 , G06F9/54 , G06N5/022
Abstract: Techniques are described for identifying an input training dataset stored within an underlying data platform; and transmitting instructions to the data platform, the instructions being executable by the data platform to train a predictive model based on the input training dataset by delegating one or more data processing operations to a plurality of nodes across the data platform.
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公开(公告)号:US11681715B2
公开(公告)日:2023-06-20
申请号:US17342812
申请日:2021-06-09
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Paul O'Hara , Malte Christian Kaufmann , Anirban Banerjee , Ian Denver , Alan McShane
IPC: G06F16/2458 , G06F16/28
CPC classification number: G06F16/2462 , G06F16/2465 , G06F16/285
Abstract: Systems and methods include determination, determine, for each of a plurality of discrete features, of statistics for each discrete value of the discrete feature based on values of a continuous feature associated with the discrete value, determination, for each discrete feature, of first summary statistics based on the statistics determined for each discrete value of the discrete feature, determination, for each discrete feature, of a dissimilarity based on the first summary statistics determined for the discrete feature and on the statistics determined for each discrete value of the discrete feature, determination of candidate discrete features of the discrete features based on the determined dissimilarities, the candidate discrete features comprising less than all of the discrete features, determination, for each of the candidate discrete features, of second summary statistics based on values of the continuous feature associated with each discrete value of the candidate discrete feature, determine of a deviation score for each of the candidate discrete features based on the second summary statistics, and presentation of the candidate discrete features based on the determined deviation scores.
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公开(公告)号:US11675765B2
公开(公告)日:2023-06-13
申请号:US17329519
申请日:2021-05-25
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Ying Wu , Malte Christian Kaufmann , Alan McShane , Anirban Banerjee , Gareth Maguire
IPC: G06F16/22 , G06F18/2113 , G06F18/2321 , G06F18/23213
CPC classification number: G06F16/2237 , G06F16/2264 , G06F18/2113 , G06F18/2321 , G06F18/23213
Abstract: A system and method including determining, for a specified target measure column of a first dataset including a plurality of records, the metadata of the first dataset, including a probability distribution for the specified target column and dimension scores for the dimensions for the first dataset conditioned on the specified target measure column, where the first dataset comprises a plurality of columns including the at least one target measure column and a plurality of non-numeric, dimension columns for the records of the first dataset; determining, for a subset of data of the first dataset based on one or more specified variables, dimension scores for the dimensions of the subset of data approximately derived from the determined metadata of the first dataset; and providing recommendations of top contributors based on the approximated dimension scores of dimensions of the subset of data.
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公开(公告)号:US11574019B2
公开(公告)日:2023-02-07
申请号:US16134043
申请日:2018-09-18
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Apoorva Kumar , Alan McShane
IPC: G06F16/9038 , G06F3/0486 , G06F16/25 , G06N20/00
Abstract: Techniques are described for integrating prediction capabilities from data management platforms into applications. Implementations employ a data science platform (DSP) that operates in conjunction with a data management solution (e.g., a data hub). The DSP can be used to orchestrate data pipelines using various machine learning (ML) algorithms and/or data preparation functions. The data hub can also provide various orchestration and data pipelining capabilities to receive and handle data from various types of data sources, such as databases, data warehouses, other data storage solutions, internet-of-things (IoT) platforms, social networks, and/or other data sources. In some examples, users such as data engineers and/or others may use the implementations described herein to handle the orchestration of data into a data management platform.
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公开(公告)号:US20220382729A1
公开(公告)日:2022-12-01
申请号:US17329519
申请日:2021-05-25
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor: Ying Wu , Malte Christian Kaufmann , Alan McShane , Anirban Banerjee , Gareth Maguire
Abstract: A system and method including determining, for a specified target measure column of a first dataset including a plurality of records, the metadata of the first dataset, including a probability distribution for the specified target column and dimension scores for the dimensions for the first dataset conditioned on the specified target measure column, where the first dataset comprises a plurality of columns including the at least one target measure column and a plurality of non-numeric, dimension columns for the records of the first dataset; determining, for a subset of data of the first dataset based on one or more specified variables, dimension scores for the dimensions of the subset of data approximately derived from the determined metadata of the first dataset; and providing recommendations of top contributors based on the approximated dimension scores of dimensions of the subset of data.
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公开(公告)号:US10789547B2
公开(公告)日:2020-09-29
申请号:US15261215
申请日:2016-09-09
Applicant: Business Objects Software Ltd.
Inventor: Alan McShane , Jacques Doan Huu , Ahmed Abdelrahman , Antoine Carme , Bertrand Lamy , Fadi Maali , Laya Ouologuem , Milena Caires , Nicolas Dulian , Erik Marcade
Abstract: Techniques are described for identifying an input training dataset stored within an underlying data platform; and transmitting instructions to the data platform, the instructions being executable by the data platform to train a predictive model based on the input training dataset by delegating one or more data processing operations to a plurality of nodes across the data platform.
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