公开(公告)号：USD802000S1

公开(公告)日：2017-11-07

申请号：US29569704

申请日：2016-06-29

Applicant: Palantir Technologies Inc.

Designer： Jack Grossman ,  Antoine Llorca ,  Gregory Martin ,  Alessandro Mingione ,  Marvin Sum

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：USD779503S1

公开(公告)日：2017-02-21

申请号：US29508336

申请日：2014-11-05

Applicant: Palantir Technologies Inc.

Designer： Marvin Sum ,  Joshua Goldenberg ,  Adam Torres ,  Antoine Llorca ,  Piotr Kwiatkowski

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：US20210385237A1

公开(公告)日：2021-12-09

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: 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.

公开(公告)号：US10447712B2

公开(公告)日：2019-10-15

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: G06Q40/00 ,  H04L29/06 ,  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：US09589299B2

公开(公告)日：2017-03-07

申请号：US15151904

申请日：2016-05-11

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 ,  G06F3/0482 ,  G06F3/0484 ,  G06F12/10 ,  G06F17/30 ,  G06K9/62

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：US09367872B1

公开(公告)日：2016-06-14

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 ,  Vicktoria Lai ,  Steven Berler ,  Alexei Smaliy ,  Suchan Lee

IPC: G06Q40/00 ,  G06F12/10 ,  G06F17/30 ,  G06K9/62

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：US09298678B2

公开(公告)日：2016-03-29

申请号：US14326738

申请日：2014-07-09

Applicant: PALANTIR TECHNOLOGIES INC.

Inventor： John Chakerian ,  Robert Fink ,  Mark Schafer ,  James Thompson ,  Marvin Sum ,  Allen Cai

IPC: G06F7/02 ,  G06F17/30 ,  G06F17/21 ,  G06F3/0484

CPC classification number: G06F17/30598 ,  G06F3/0482 ,  G06F3/04842 ,  G06F17/212 ,  G06F17/30011 ,  G06F17/30386 ,  G06F17/3053 ,  G06F17/30601 ,  G06F17/30705 ,  G06F17/3071 ,  G06F17/30867

Abstract: Systems and methods are disclosed for news events detection and visualization. In accordance with one implementation, a method is provided for news events detection and visualization. The method includes, for example, obtaining one or more user inputs, determining, based on the user inputs, an entity and a date range, obtaining one or more documents associated with the entity and with dates within the date range, the one or more documents being grouped into one or more clusters, and the clusters being grouped into one or more megaclusters, and presenting the one or more documents on one or more timelines, wherein the one or more documents are grouped into different megaclusters being presented in a visually distinct way. The method further allows for filtering of the one or more clusters based on a value associated with the one or more clusters.

Abstract translation: 公开了用于新闻事件检测和可视化的系统和方法。 根据一个实现，提供了一种用于新闻事件检测和可视化的方法。 该方法包括例如获得一个或多个用户输入，基于用户输入确定实体和日期范围，获得与该实体相关联的一个或多个文档以及日期范围内的日期，所述一个或多个 文档被分组成一个或多个集群，并且所述集群被分组成一个或多个巨集群，并且在一个或多个时间线上呈现一个或多个文档，其中所述一个或多个文档被分组成以视觉上不同的方式呈现的不同的巨集群 办法。 该方法还允许基于与一个或多个集群相关联的值来过滤一个或多个集群。

公开(公告)号：US09256664B2

公开(公告)日：2016-02-09

申请号：US14323935

申请日：2014-07-03

Applicant: PALANTIR TECHNOLOGIES INC.

Inventor： John Chakerian ,  Robert Fink ,  Mark Schafer ,  James Thompson ,  Marvin Sum ,  Allen Cai

IPC: G06F7/02 ,  G06F17/30

CPC classification number: G06F17/30598 ,  G06F3/0482 ,  G06F3/04842 ,  G06F17/212 ,  G06F17/30011 ,  G06F17/30386 ,  G06F17/3053 ,  G06F17/30601 ,  G06F17/30705 ,  G06F17/3071 ,  G06F17/30867

Abstract: Systems and methods are disclosed for news events detection and visualization. In accordance with one implementation, a method is provided for news events detection and visualization. The method includes, for example, obtaining a document, obtaining from the document a plurality of tokens, obtaining a document vector based on a plurality of frequencies associated with the plurality of tokens, obtaining one or more clusters of documents, each cluster associated with a plurality of documents and a cluster vector, determining a matching cluster from the one or more clusters based at least on the similarity between the document vector and the cluster vector of the matching cluster, and updating a database to associate the document with the matching cluster.

Abstract translation: 公开了用于新闻事件检测和可视化的系统和方法。 根据一个实现，提供了一种用于新闻事件检测和可视化的方法。 该方法包括例如获得文档，从文档获得多个令牌，基于与多个令牌相关联的多个频率获得文档向量，获得一个或多个文档簇，每个与 多个文档和群集向量，至少基于所述文档向量与所述匹配群集的簇向量之间的相似度，从所述一个或多个群集确定匹配群集，以及更新数据库以使所述文档与所述匹配群集相关联。