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    PROVIDER PORTAL
    3.
    发明申请
    PROVIDER PORTAL 审中-公开

    公开(公告)号：US20180082031A1

    公开(公告)日：2018-03-22

    申请号：US15826284

    申请日：2017-11-29

    申请人： Palantir Technologies Inc.

    发明人： Sam Fendell ,  James Thompson

    IPC分类号： G06F19/00 ,  G06Q50/24 ,  G06Q40/08 ,  G06Q50/22

    CPC分类号： G06F19/328 ,  G06Q40/08 ,  G06Q50/22 ,  G06Q50/24 ,  G16H10/60

    摘要： Various systems and methods are provided that graphically allow health insurance company personnel to identify patient diagnoses that are not accounted for by the health insurance company. Furthermore, the various systems and methods graphically allow health insurance company personnel to identify patients that have not submitted claims for documented ailments or conditions. Thus, the health insurance company may be able to improve its chances of receiving transfer payments from other health insurance companies and/or receiving higher star ratings.

    INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS
    6.
    发明申请
    INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS 有权
    内部恶意数据项集合和分析

    公开(公告)号：US20160006749A1

    公开(公告)日：2016-01-07

    申请号：US14486991

    申请日：2014-09-15

    申请人： Palantir Technologies Inc.

    发明人： 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分类号： H04L29/06 ,  G06F17/30

    CPC分类号： H04L63/1425 ,  G06F17/30598 ,  G06Q40/12 ,  H04L63/1408 ,  H04L63/145

    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, 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.

    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，并以优化的方式向分析者提供自动化分析的结果。 集群数据结构（本文中也称为数据集群）的自动化分析可以包括各种标准或规则的自动应用，以便生成数据集群的紧凑的，人类可读的分析。 可以将数据集群的可读分析（也称为“摘要”或“结论”）组织成交互式用户界面，以使分析人员能够在与各种数据集群相关联的信息之间快速导航，并有效地评估 这些数据集群在例如欺诈调查的背景下。 本公开的实施例还涉及聚类数据结构的自动评分。

    Systems and methods for active column filtering
    7.
    发明授权
    Systems and methods for active column filtering 有权
    主动列过滤的系统和方法

    公开(公告)号：US09009171B1

    公开(公告)日：2015-04-14

    申请号：US14268964

    申请日：2014-05-02

    申请人： Palantir Technologies, Inc.

    发明人： Jack Grossman ,  James Thompson

    IPC分类号： G06F17/30

    CPC分类号： G06F17/245 ,  G06F3/0482 ,  G06F17/218 ,  G06F17/30315 ,  G06F17/30339 ,  G06F17/3056 ,  G06F17/30864 ,  G06F17/30997

    摘要： Systems and methods are disclosed for active column filtering. In accordance with one implementation, a method is provided for active column filtering. The method includes providing a table having data values arranged in rows and columns, providing a first filter location indicator whose location is visually associated with a first column, and providing a first interface based on a selection of the first filter location indicator, wherein the first interface's location is visually associated with the first column. The method also includes acquiring a first filter input entered into the first interface, filtering the table based on the acquired first filter input, providing the filtered table for displaying, and providing an applied filter indicator, whose location is visually associated with the first column, the applied filter indicator including at least the first filter input.

    摘要翻译： 公开了用于活性柱过滤的系统和方法。 根据一个实现，提供了一种用于主动列过滤的方法。 该方法包括提供具有以行和列排列的数据值的表，提供其位置与第一列可视地相关联的第一过滤器位置指示符，以及基于第一过滤器位置指示符的选择来提供第一接口，其中第一 界面的位置与第一列视觉相关联。 该方法还包括获取输入到第一接口中的第一过滤器输入，基于所获取的第一过滤器输入来过滤表，提供用于显示的过滤表，并提供其位置与第一列视觉相关联的应用过滤器指示符， 应用的滤波器指示器至少包括第一滤波器输入。

    Propagated deletion of database records and derived data
    9.
    发明授权
    Propagated deletion of database records and derived data 有权

    公开(公告)号：US11822542B2

    公开(公告)日：2023-11-21

    申请号：US17208914

    申请日：2021-03-22

    申请人： Palantir Technologies Inc.

    发明人： Jeppe Hallgren ,  Ammaar Reshi ,  James Thompson

    IPC分类号： G06F16/23 ,  G06F16/24 ,  G06F16/25 ,  G06F16/242

    CPC分类号： G06F16/2386 ,  G06F16/2365 ,  G06F16/2433 ,  G06F16/254

    摘要： In an embodiment, a data processing method comprises, using a distributed database system that is programmed to manage a plurality of different raw datasets and a plurality of derived datasets that have been derived from the raw datasets based on a plurality of derivation relationships that link the raw datasets to the derived datasets: from a first dataset that is stored in the distributed database system, determining a subset of records that are candidates for propagated deletion of specified data values; determining one or more particular raw datasets that contain the subset of records; deleting the specified data values from the particular raw datasets; based on the plurality of derivation relationships and the particular raw datasets, identifying one or more particular derived datasets that have been derived from the particular raw datasets; generating and executing a build of the one or more particular derived datasets to result in creating and storing the one or more particular derived datasets without the specified data values that were deleted from the particular raw datasets; repeating the generating and executing for all derived datasets that have derivation relationships to the particular raw datasets; wherein the method is performed using one or more processors.