公开(公告)号：US11727481B2

公开(公告)日：2023-08-15

申请号：US17445439

申请日：2021-08-19

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal ,  James Thompson ,  Marvin Sum ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Devin Witherspoon ,  Victoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: 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 classification number: 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

Abstract: 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.

公开(公告)号：US20170237755A1

公开(公告)日：2017-08-17

申请号：US15419718

申请日：2017-01-30

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal

IPC: H04L29/06

CPC classification number: H04L63/1416 ,  H04L63/0209 ,  H04L63/0236 ,  H04L63/0272 ,  H04L63/101 ,  H04L63/14 ,  H04L63/1408 ,  H04L63/1425 ,  H04L63/1433 ,  H04L63/1441 ,  H04L63/145

Abstract: Systems and methods are presented for generating a threat score and a usage score of each of a plurality of IP addresses. The threat score may be determined based on quantity of occurrences and recency of each occurrence of an IP address in network alert datasets, in addition to a weighting factor for each data source indicating the accuracy of the data source.

公开(公告)号：US11102224B2

公开(公告)日：2021-08-24

申请号：US16553971

申请日：2019-08-28

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal ,  James Thompson ,  Marvin Sum ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Devin Witherspoon ,  Victoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: H04L29/06 ,  G06Q40/00 ,  G06F16/28 ,  G06F16/9038 ,  G06F16/2457 ,  G06F3/0482 ,  G06F3/0484 ,  G06Q40/02 ,  G06F12/1036 ,  G06K9/62 ,  G06F16/34 ,  G06F21/55

Abstract: 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.

公开(公告)号：US20190079980A1

公开(公告)日：2019-03-14

申请号：US15711712

申请日：2017-09-21

Applicant: PALANTIR TECHNOLOGIES INC.

Inventor： AMR AL MALLAH ,  Alexander Visbal ,  David Philipson ,  James Thompson ,  Natasha D'Souza ,  Ryan Xie ,  Wayne Chen Spiegel

IPC: G06F17/30 ,  G06F9/44

Abstract: In one embodiment, a data processing method comprises, using a first computer, in response to detecting a change in a data source: automatically generating a dataset comprising a subset of data from the data source, generating a unique dataset identifier, and associating the dataset identifier with the dataset in digital data storage; generating a display description that comprises: the dataset identifier; and for each particular graphical data display widget among one or more graphical data display widgets, instructions that specify a widget type, an order and one or more widget configuration values for the particular graphical data display widget; transmitting the display description to a second computer.

公开(公告)号：US08832832B1

公开(公告)日：2014-09-09

申请号：US14147402

申请日：2014-01-03

Applicant: Palantir Technologies, Inc.

Inventor： Alexander Visbal

IPC: G06F21/00 ,  H04L29/06

CPC classification number: H04L63/1416 ,  H04L63/0209 ,  H04L63/0236 ,  H04L63/0272 ,  H04L63/101 ,  H04L63/14 ,  H04L63/1408 ,  H04L63/1425 ,  H04L63/1433 ,  H04L63/1441 ,  H04L63/145

Abstract: Systems and methods are presented for generating a threat score and a usage score of each of a plurality of IP addresses. The threat score may be determined based on quantity of occurrences and recency of each occurrence of an IP address in network alert datasets, in addition to a weighting factor for each data source indicating the accuracy of the data source.

Abstract translation: 呈现系统和方法用于生成威胁得分和多个IP地址中的每一个的使用分数。 除了表示数据源的准确性的每个数据源的加权因子之外，还可以基于网络警报数据集中每次出现IP地址的出现次数和近似度来确定威胁分数。

公开(公告)号：US11580472B2

公开(公告)日：2023-02-14

申请号：US15097842

申请日：2016-04-13

Applicant: Palantir Technologies Inc.

Inventor： Kevin Richards ,  Arseny Bogomolov ,  Grigory Bonik ,  Victor Hsu ,  Alexander Visbal ,  John Carrino ,  Cooper Bills ,  Diran Li ,  William Rhyne ,  Timothy O'Brien ,  Matthew Bango

IPC: G06Q10/06 ,  G06Q50/18 ,  G06F16/93 ,  G06Q10/10 ,  G06Q10/0631

Abstract: A case management system is configured to provide one or more case generation and management functions. As configured, the case management system enables a user to define a workflow, the workflow including one or more states, one or more operations which may be performed at the one or more states, and one or more transitions corresponding to the operations and defining a sequence of the states; to generate and configure a state machine; to receive a workflow identifier to assign to the state machine; and through a command received from a client device, to open and manage a case based on the configuration of the state machine.

公开(公告)号：US20170244735A1

公开(公告)日：2017-08-24

申请号：US15449042

申请日：2017-03-03

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal ,  James Thompson ,  Marvin Sum ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Devin Witherspoon ,  Victoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: H04L29/06 ,  G06F17/30 ,  G06Q40/02

CPC classification number: 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

Abstract: 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.

公开(公告)号：US09560066B2

公开(公告)日：2017-01-31

申请号：US14816748

申请日：2015-08-03

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal

IPC: G06F21/00 ,  H04L29/06

CPC classification number: H04L63/1416 ,  H04L63/0209 ,  H04L63/0236 ,  H04L63/0272 ,  H04L63/101 ,  H04L63/14 ,  H04L63/1408 ,  H04L63/1425 ,  H04L63/1433 ,  H04L63/1441 ,  H04L63/145

Abstract: Systems and methods are presented for generating a threat score and a usage score of each of a plurality of IP addresses. The threat score may be determined based on quantity of occurrences and recency of each occurrence of an IP address in network alert datasets, in addition to a weighting factor for each data source indicating the accuracy of the data source.

Abstract translation: 呈现系统和方法用于生成威胁得分和多个IP地址中的每一个的使用分数。 除了表示数据源的准确性的每个数据源的加权因子之外，还可以基于网络警报数据集中每次出现IP地址的出现次数和近似度来确定威胁分数。

公开(公告)号：US20160180451A1

公开(公告)日：2016-06-23

申请号：US14579752

申请日：2014-12-22

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal ,  James Thompson ,  Marvin Sum ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Devin Witherspoon ,  Victoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: G06Q40/00

CPC classification number: 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

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20190387008A1

公开(公告)日：2019-12-19

申请号：US16553971

申请日：2019-08-28

Applicant: Palantir Technologies Inc.

Inventor： Alexander Visbal ,  James Thompson ,  Marvin Sum ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Devin Witherspoon ,  Victoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: H04L29/06 ,  G06Q40/00 ,  G06F16/28 ,  G06F16/9038 ,  G06F16/2457 ,  G06F3/0482 ,  G06F3/0484 ,  G06Q40/02

Abstract: 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.