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公开(公告)号：US11727481B2
公开(公告)日：2023-08-15
申请号：US17445439
申请日：2021-08-19
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： G06Q40/00 , G06F16/28 , G06F16/9038 , G06F16/2457 , G06F3/0482 , G06F3/04842 , G06Q40/02 , H04L9/40 , G06F12/1036 , G06F16/34 , G06F18/23 , G06F18/40 , G06F21/55
CPC分类号： G06Q40/00 , G06F3/0482 , G06F3/04842 , G06F16/24578 , G06F16/287 , G06F16/9038 , G06Q40/02 , H04L63/1416 , H04L63/1425 , H04L63/1433 , G06F12/1036 , G06F16/34 , G06F18/23 , G06F18/40 , G06F21/552
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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公开(公告)号：US11102224B2
公开(公告)日：2021-08-24
申请号：US16553971
申请日：2019-08-28
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： H04L29/06 , G06Q40/00 , G06F16/28 , G06F16/9038 , G06F16/2457 , G06F3/0482 , G06F3/0484 , G06Q40/02 , G06F12/1036 , G06K9/62 , G06F16/34 , G06F21/55
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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公开(公告)号：US20190387008A1
公开(公告)日：2019-12-19
申请号：US16553971
申请日：2019-08-28
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： H04L29/06 , G06Q40/00 , G06F16/28 , G06F16/9038 , G06F16/2457 , G06F3/0482 , G06F3/0484 , G06Q40/02
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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公开(公告)号：US20160253750A1
公开(公告)日：2016-09-01
申请号：US15151904
申请日：2016-05-11
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： G06Q40/00 , G06F3/0482 , G06F3/0484 , G06F17/30
CPC分类号： H04L63/1416 , G06F3/0482 , G06F3/04842 , G06F12/1036 , G06F17/3053 , G06F17/30601 , G06F17/30716 , G06F17/30991 , G06F21/552 , G06K9/6218 , G06K9/6253 , G06Q40/00 , G06Q40/02 , H04L63/1425 , H04L63/1433
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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公开(公告)号：US20170244735A1
公开(公告)日：2017-08-24
申请号：US15449042
申请日：2017-03-03
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
CPC分类号： H04L63/1416 , G06F3/0482 , G06F3/04842 , G06F12/1036 , G06F16/24578 , G06F16/287 , G06F16/34 , G06F16/9038 , G06F21/552 , G06K9/6218 , G06K9/6253 , G06Q40/00 , G06Q40/02 , H04L63/1425 , H04L63/1433
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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6.发明申请SYSTEMS AND USER INTERFACES FOR DYNAMIC AND INTERACTIVE INVESTIGATION OF BAD ACTOR BEHAVIOR BASED ON AUTOMATIC CLUSTERING OF RELATED DATA IN VARIOUS DATA STRUCTURES 有权基于各种数据结构中相关数据自动聚类的行为行为的动态和交互式调查的系统和用户界面公开(公告)号：US20160180451A1
公开(公告)日：2016-06-23
申请号：US14579752
申请日：2014-12-22
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： G06Q40/00
CPC分类号： H04L63/1416 , G06F3/0482 , G06F3/04842 , G06F12/1036 , G06F17/3053 , G06F17/30601 , G06F17/30716 , G06F17/30991 , G06F21/552 , G06K9/6218 , G06K9/6253 , G06Q40/00 , G06Q40/02 , H04L63/1425 , H04L63/1433
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
摘要翻译： 本公开的实施例涉及一种数据分析系统，其可以自动生成存储器有效的集群数据结构，自动分析这些集群数据结构，自动标记和分组这些集群数据结构，并且提供自动化分析和分组的结果。 分析师的方式。 集群数据结构（本文也称为数据集群）的自动分析可以包括各种标准或规则的自动化应用，以便生成相关数据集群组的平铺显示，使得分析者可以快速有效地评估 数据集群。 特别地，可以在交互式用户界面中动态地重新分组和/或过滤数据集群，以便分析人员可以在与各种数据集群相关联的信息之间快速导航，并在上下文中有效地评估那些数据集群 例如欺诈调查。
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公开(公告)号：US20210385237A1
公开(公告)日：2021-12-09
申请号：US17445439
申请日：2021-08-19
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： H04L29/06 , G06Q40/00 , G06F16/28 , G06F16/9038 , G06F16/2457 , G06F3/0482 , G06F3/0484 , G06Q40/02
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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公开(公告)号：US10447712B2
公开(公告)日：2019-10-15
申请号：US15449042
申请日：2017-03-03
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： G06Q40/00 , H04L29/06 , G06F16/28 , G06F16/9038 , G06F16/2457 , G06F3/0482 , G06F3/0484 , G06Q40/02 , G06F12/1036 , G06K9/62 , G06F16/34 , G06F21/55
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
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9.发明授权Systems and user interfaces for dynamic and interactive investigation of bad actor behavior based on automatic clustering of related data in various data structures 有权基于各种数据结构中相关数据的自动聚类，对不良行为行为进行动态和交互式调查的系统和用户界面公开(公告)号：US09589299B2
公开(公告)日：2017-03-07
申请号：US15151904
申请日：2016-05-11
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Victoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
IPC分类号： G06Q40/00 , G06F3/0482 , G06F3/0484 , G06F12/10 , G06F17/30 , G06K9/62
CPC分类号： H04L63/1416 , G06F3/0482 , G06F3/04842 , G06F12/1036 , G06F17/3053 , G06F17/30601 , G06F17/30716 , G06F17/30991 , G06F21/552 , G06K9/6218 , G06K9/6253 , G06Q40/00 , G06Q40/02 , H04L63/1425 , H04L63/1433
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
摘要翻译： 本公开的实施例涉及一种数据分析系统，其可以自动生成存储器有效的集群数据结构，自动分析这些集群数据结构，自动标记和分组这些集群数据结构，并且提供自动化分析和分组的结果。 分析师的方式。 集群数据结构（本文也称为数据集群）的自动分析可以包括各种标准或规则的自动化应用，以便生成相关数据集群组的平铺显示，使得分析者可以快速有效地评估 数据集群。 特别地，可以在交互式用户界面中动态地重新分组和/或过滤数据集群，以便分析人员可以在与各种数据集群相关联的信息之间快速导航，并在上下文中有效地评估那些数据集群 例如欺诈调查。
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10.发明授权Systems and user interfaces for dynamic and interactive investigation of bad actor behavior based on automatic clustering of related data in various data structures 有权基于各种数据结构中相关数据的自动聚类，对不良行为行为进行动态和交互式调查的系统和用户界面公开(公告)号：US09367872B1
公开(公告)日：2016-06-14
申请号：US14579752
申请日：2014-12-22
发明人： Alexander Visbal , James Thompson , Marvin Sum , Jason Ma , Bing Jie Fu , Ilya Nepomnyashchiy , Devin Witherspoon , Vicktoria Lai , Steven Berler , Alexei Smaliy , Suchan Lee
CPC分类号： H04L63/1416 , G06F3/0482 , G06F3/04842 , G06F12/1036 , G06F17/3053 , G06F17/30601 , G06F17/30716 , G06F17/30991 , G06F21/552 , G06K9/6218 , G06K9/6253 , G06Q40/00 , G06Q40/02 , H04L63/1425 , H04L63/1433
摘要： Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.
摘要翻译： 本公开的实施例涉及一种数据分析系统，其可以自动生成存储器有效的集群数据结构，自动分析这些集群数据结构，自动标记和分组这些集群数据结构，并且提供自动化分析和分组的结果。 分析师的方式。 集群数据结构（本文也称为数据集群）的自动分析可以包括各种标准或规则的自动化应用，以便生成相关数据集群组的平铺显示，使得分析者可以快速有效地评估 数据集群。 特别地，可以在交互式用户界面中动态地重新分组和/或过滤数据集群，以便分析人员可以在与各种数据集群相关联的信息之间快速导航，并在上下文中有效地评估那些数据集群 例如欺诈调查。
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