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。

公开(公告)号：US20150135052A1

公开(公告)日：2015-05-14

申请号：US14479160

申请日：2014-09-05

Applicant: Palantir Technologies Inc.

Inventor： James Thompson ,  Joshua Goldenberg

IPC: G06F17/24 ,  G06F3/0484 ,  G06F3/0481

Abstract: The display of a multi-column table can be optimized. For example, a container, such as a multi-column table, can have a first container width. The container includes first text, second text, and a divider, such as an icon, whitespace, or text, between the first text and the second text. The first text, the second text, and the divider can have a combined text width. The container can be resized to a second container width that is smaller than the first container width. If it is determined that the combined text width is then greater than the second container width, the first text, the second text, or both can be abbreviated until the combined text width is less than the second container width.

Abstract translation: 可以优化多列表的显示。 例如，诸如多列表的容器可以具有第一容器宽度。 容器包括第一文本和第二文本之间的第一文本，第二文本和分隔符，诸如图标，空格或文本。 第一个文本，第二个文本和分隔符可以具有组合的文本宽度。 容器可以调整到小于第一容器宽度的第二容器宽度。 如果确定组合的文本宽度大于第二容器宽度，则可以缩短第一文本，第二文本或两者，直到组合的文本宽度小于第二容器宽度。

公开(公告)号：US11775898B1

公开(公告)日：2023-10-03

申请号：US16681051

申请日：2019-11-12

Applicant: Palantir Technologies Inc.

Inventor： James Thompson ,  Joseph Rafidi ,  Patrick Szmucer

IPC: G06Q10/0631 ,  G06F16/906 ,  G06F16/904 ,  G06F16/16 ,  G06F16/901 ,  G06N7/01

CPC classification number: G06Q10/06315 ,  G06F16/168 ,  G06F16/904 ,  G06F16/906 ,  G06F16/9024 ,  G06N7/01

Abstract: A resource dependency system and its associated user interfaces, used for tracking data dependencies and data transformations between resources, may display visual node graphs with resources as nodes and the data dependencies and data transformations associated with the columns as edges between the nodes. The nodes representing the resources may be displayed differently based on relevant differences in the resources they represent, which can be set through various selectable criteria and schemes. The user interfaces may include selectable options for visually arranging the nodes or grouping the nodes into superseding nodes according to how the nodes are displayed or the relevant differences in the resources they represent. Updated properties and data dependencies associated with superseding nodes can be presented to the user.

公开(公告)号：US11257263B1

公开(公告)日：2022-02-22

申请号：US16598804

申请日：2019-10-10

Applicant: Palantir Technologies Inc.

Inventor： Salar Al Khafaji ,  James Thompson ,  Joseph Hashim ,  Joseph Rafidi ,  Parvathy Menon ,  Patrick Szmucer ,  Robert Kruszewski ,  Slawomir Mucha ,  Tyler Uhlenkamp ,  Vilmos Ioo

IPC: G06T3/40 ,  G06T11/20

Abstract: In some embodiments, a method comprises obtaining a pipeline of operations, the pipeline of operations including a plurality of functions providing any of one or more modification operations or visualization operations for a plurality of datasets. A first dynamic visualization of the pipeline of operations at a first level of granularity is generated. A second dynamic visualization of the pipeline of operations at a second level of granularity is generated in response to user input.

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：US10798116B2

公开(公告)日：2020-10-06

申请号：US15961431

申请日：2018-04-24

Applicant: Palantir Technologies Inc.

Inventor： David Cohen ,  Jason Ma ,  Bing Jie Fu ,  Ilya Nepomnyashchiy ,  Steven Berler ,  Alex Smaliy ,  Jack Grossman ,  James Thompson ,  Julia Boortz ,  Matthew Sprague ,  Parvathy Menon ,  Michael Kross ,  Michael Harris ,  Adam Borochoff

IPC: G06F21/00 ,  H04L29/06 ,  G06Q40/00 ,  G06F16/28 ,  G06F21/56 ,  H04L12/40

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, and provide results of the automated analysis 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 compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

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.