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Patent Agency Ranking
公开(公告)号：US11562002B2
公开(公告)日：2023-01-24
申请号：US16256519
申请日：2019-01-24
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor： Paul Pallath , Rouzbeh Razavi
IPC: G06F16/28 , G06F16/2458
Abstract: The present disclosure describes methods, systems, and computer program products for enabling advanced analytics with large datasets. One computer-implemented method includes receiving, by operation of a computer system, a dataset of multiple data records, each of the plurality of data records comprising one or more features and a target variable; selecting key features among the one or more features based at least on relevance measures of the one or more features with respect to the target variable; dividing the dataset into multiple subsets; for each of the multiple subsets, identifying a number of clusters and respective centroids of the number of clusters based on the key features; identifying a number of final centroids based on the respective centroids of the number of clusters for the each of the number of subsets, the number of final centroids being respective centroids of a number of final clusters; and for each data record in the multiple subsets, assigning the data record to one of the number of final clusters based on distances between the data record and the number of final centroids.
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公开(公告)号：US20190155824A1
公开(公告)日：2019-05-23
申请号：US16256519
申请日：2019-01-24
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor： Paul Pallath , Rouzbeh Razavi
IPC: G06F16/28 , G06F16/2458
Abstract: The present disclosure describes methods, systems, and computer program products for enabling advanced analytics with large datasets. One computer-implemented method includes receiving, by operation of a computer system, a dataset of multiple data records, each of the plurality of data records comprising one or more features and a target variable; selecting key features among the one or more features based at least on relevance measures of the one or more features with respect to the target variable; dividing the dataset into multiple subsets; for each of the multiple subsets, identifying a number of clusters and respective centroids of the number of clusters based on the key features; identifying a number of final centroids based on the respective centroids of the number of clusters for the each of the number of subsets, the number of final centroids being respective centroids of a number of final clusters; and for each data record in the multiple subsets, assigning the data record to one of the number of final clusters based on distances between the data record and the number of final centroids.
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公开(公告)号：US10013303B2
公开(公告)日：2018-07-03
申请号：US15496348
申请日：2017-04-25
Applicant: Business Objects Software Ltd.
Inventor： Paul Pallath , Rouzbeh Razavi
CPC classification number: G06F11/079 , G05B23/02 , G05B23/0254 , G06F11/0709 , G06F11/0751 , G06F11/0787 , H04L67/12
Abstract: The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.
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公开(公告)号：US10037025B2
公开(公告)日：2018-07-31
申请号：US14877764
申请日：2015-10-07
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor： Paul Pallath , Rouzbeh Razavi
CPC classification number: G06F11/079 , G05B23/02 , G05B23/0254 , G06F11/0709 , G06F11/0751 , G06F11/0787 , H04L67/12
Abstract: The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.
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公开(公告)号：US20170102978A1
公开(公告)日：2017-04-13
申请号：US14877764
申请日：2015-10-07
Applicant: BUSINESS OBJECTS SOFTWARE LTD.
Inventor： Paul Pallath , Rouzbeh Razavi
IPC: G06F11/07
CPC classification number: G05B23/02 , G05B23/0254 , G06F11/0709 , G06F11/0751 , G06F11/0787 , G06F11/079 , H04L67/12
Abstract: The present disclosure describes methods, systems, and computer program products for detecting anomalies in an Internet-of-Things (IoT) network. One computer-implemented method includes receiving, by operation of a computer system, a dataset of a plurality of data records, each of the plurality of data records comprising a plurality of features and a target variable, the plurality of features and target variable including information of a manufacturing environment; identifying a set of normal data records from the dataset based on the target variable; identifying inter-feature correlations by performing correlation analysis on the set of normal data records; and detecting anomaly based on the inter-feature correlations for predictive maintenance.
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