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    System and method for collocation detection
    12.
    发明授权
    System and method for collocation detection 有权
    搭配检测的系统和方法

    公开(公告)号：US09503844B1

    公开(公告)日：2016-11-22

    申请号：US14088251

    申请日：2013-11-22

    Applicant: PALANTIR TECHNOLOGIES, INC.

    Inventor： Matthew Sprague ,  Miklos Danka ,  Bill Dwyer

    IPC: H04M11/04 ,  H04W4/02 ,  H04W12/02 ,  H04L29/08

    CPC classification number: H04W4/02 ,  H04L63/1425 ,  H04L63/30 ,  H04L67/22 ,  H04W12/02

    Abstract: Systems and methods are disclosed for collocation detection. In accordance with one implementation, a method is provided for collocation detection. The method includes obtaining a first object observation that includes a first object identifier, a first observation time, and a first observation location. The method also includes obtaining a second object observation that includes a second object identifier, a second observation time, and a second observation location. In addition, the method includes associating the first observation with a first area on a map, associating the second observation with a second area on the map, and determining whether a potential meeting occurred between objects associated with the first object identifier and the second object identifier based on the first and second observation times, and the first and second areas.

    Abstract translation: 公开了用于搭配检测的系统和方法。 根据一个实现，提供了一种用于搭配检测的方法。 该方法包括获得包括第一对象标识符，第一观察时间和第一观察位置的第一对象观察。 该方法还包括获得包括第二对象标识符，第二观察时间和第二观察位置的第二对象观察。 此外，该方法包括将第一观察与地图上的第一区域相关联，将第二观测与地图上的第二区域相关联，以及确定与第一对象标识符相关联的对象与第二对象标识符之间是否发生潜在会议 基于第一和第二观察时间，以及第一和第二区域。

    Prioritizing data clusters with customizable scoring strategies
    13.
    发明授权
    Prioritizing data clusters with customizable scoring strategies 有权

    公开(公告)号：US08712906B1

    公开(公告)日：2014-04-29

    申请号：US13968213

    申请日：2013-08-15

    Applicant: Palantir Technologies, Inc.

    Inventor： Matthew Sprague ,  Michael Kross ,  Adam Borochoff ,  Parvathy Menon ,  Michael Harris

    IPC: G06Q40/00

    Abstract: Techniques are disclosed for prioritizing a plurality of clusters. Prioritizing clusters may generally include identifying a scoring strategy for prioritizing the plurality of clusters. Each cluster is generated from a seed and stores a collection of data retrieved using the seed. For each cluster, elements of the collection of data stored by the cluster are evaluated according to the scoring strategy and a score is assigned to the cluster based on the evaluation. The clusters may be ranked according to the respective scores assigned to the plurality of clusters. The collection of data stored by each cluster may include financial data evaluated by the scoring strategy for a risk of fraud. The score assigned to each cluster may correspond to an amount at risk.

    System and method for collocation detection
    16.
    发明授权
    System and method for collocation detection 有权

    公开(公告)号：US10820157B2

    公开(公告)日：2020-10-27

    申请号：US16137190

    申请日：2018-09-20

    Applicant: Palantir Technologies Inc.

    Inventor： Matthew Sprague ,  Miklos Danka ,  Bill Dwyer

    IPC: H04W4/029 ,  H04W12/02 ,  H04L29/06 ,  H04W4/02 ,  H04W12/00 ,  H04W88/08

    Abstract: Systems and methods are disclosed for collocation detection. In accordance with one implementation, a method is provided for collocation detection. The method includes obtaining a first object observation that includes a first object identifier, a first observation time, and a first observation location. The method also includes obtaining a second object observation that includes a second object identifier, a second observation time, and a second observation location. In addition, the method includes associating the first observation with a first area on a map, associating the second observation with a second area on the map, and determining whether a potential meeting occurred between objects associated with the first object identifier and the second object identifier based on the first and second observation times, and the first and second areas.

    SYSTEM AND METHOD FOR COLLOCATION DETECTION
    18.
    发明申请
    SYSTEM AND METHOD FOR COLLOCATION DETECTION 审中-公开

    公开(公告)号：US20190028840A1

    公开(公告)日：2019-01-24

    申请号：US16137190

    申请日：2018-09-20

    Applicant: Palantir Technologies Inc.

    Inventor： Matthew Sprague ,  Miklos Danka ,  Bill Dwyer

    IPC: H04W4/02 ,  H04L29/08 ,  H04W88/08

    CPC classification number: H04W4/029 ,  H04L63/1425 ,  H04L63/30 ,  H04W4/023 ,  H04W12/00503 ,  H04W12/02 ,  H04W88/08

    Abstract: Systems and methods are disclosed for collocation detection. In accordance with one implementation, a method is provided for collocation detection. The method includes obtaining a first object observation that includes a first object identifier, a first observation time, and a first observation location. The method also includes obtaining a second object observation that includes a second object identifier, a second observation time, and a second observation location. In addition, the method includes associating the first observation with a first area on a map, associating the second observation with a second area on the map, and determining whether a potential meeting occurred between objects associated with the first object identifier and the second object identifier based on the first and second observation times, and the first and second areas.

    INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS
    19.
    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

    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: H04L29/06 ,  G06F17/30

    CPC classification number: H04L63/1425 ,  G06F17/30598 ,  G06Q40/12 ,  H04L63/1408 ,  H04L63/145

    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.

    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，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。

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