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公开(公告)号：US09208159B2
公开(公告)日：2015-12-08
申请号：US14451221
申请日：2014-08-04
Applicant: PALANTIR TECHNOLOGIES, INC.
Inventor： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
CPC classification number: G06F17/30153 , G06F11/2025 , G06F17/00 , G06F17/30067 , G06F17/30091 , G06F17/30106 , G06F17/30129 , G06F17/30371 , G06F17/30528 , G06F17/30554 , G06F17/30569 , G06F17/30705 , G06F17/30867 , G06F17/30955
Abstract: A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
Abstract translation: 提出了一种数据分析系统，用于从可能的多个异构输入数据源提供细粒度的低延迟访问大容量输入数据。 输入数据被解析，可选地变换，索引并存储在水平可扩展的键值数据存储库中，在该存储库中可以使用低延迟搜索进行访问。 输入数据可以在存储之前被压缩成块，以最小化存储要求。 搜索结果以原始形式显示输入数据。 输入数据可以包括访问日志，呼叫数据记录（CDR），电子邮件消息等。该系统允许数据分析者在大小上达到多PB的非常大的动态数据集中有效地识别感兴趣的信息。 一旦确定了感兴趣的信息，大数据集的该子集可以被导入到专门的或专门的数据分析系统中以进行进一步的深入调查和上下文分析。
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公开(公告)号：US09105000B1
公开(公告)日：2015-08-11
申请号：US14304741
申请日：2014-06-13
Applicant: Palantir Technologies Inc.
Inventor： Nicholas White , Eli Bingham , Engin Ural , Jasjit Grewal
CPC classification number: G06Q10/06398 , G06F17/30303
Abstract: According to certain aspects, a computer system may be configured to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources, each of which can include various types of data, including email data, system logon data, system logoff data, badge swipe data, employee data, job processing data, etc. associated with a plurality of individuals. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system can resolve the data from each of the plurality of data sources to unique individuals of the plurality of individuals. The system can also determine an efficiency indicator based at least in part on a comparison of individuals of the unique individuals that have at least one common characteristic.
Abstract translation: 根据某些方面，计算机系统可以被配置为聚合和分析来自多个数据源的数据。 该系统可以从多个数据源获得数据，每个数据源可以包括各种类型的数据，包括电子邮件数据，系统登录数据，系统注销数据，徽章刷卡数据，员工数据，作业处理数据等 多个人。 该系统还可以将来自多个数据源中的每一个的数据转换为兼容来自多个数据源的数据的格式。 该系统可以将来自多个数据源中的每一个的数据解析成多个个体中的唯一个体。 该系统还可以至少部分地基于具有至少一个共同特征的独特个体的个体的比较来确定效率指标。
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公开(公告)号：US20220027426A1
公开(公告)日：2022-01-27
申请号：US17493205
申请日：2021-10-04
Applicant: Palantir Technologies Inc.
Inventor： Nicholas White , Eli Bingham , Engin Ural , Jasjit Grewal
IPC: G06F16/9535 , G06Q10/06 , G06F16/215 , G06F16/242 , G06F16/2457 , G06F16/34
Abstract: According to certain aspects, a computer system may be configured to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources, each of which can include various types of data, including email data, system logon data, system logoff data, badge swipe data, employee data, job processing data, etc. associated with a plurality of individuals. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system can resolve the data from each of the plurality of data sources to unique individuals of the plurality of individuals. The system can also determine an efficiency indicator based at least in part on a comparison of individuals of the unique individuals that have at least one common characteristic.
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公开(公告)号：US11138279B1
公开(公告)日：2021-10-05
申请号：US16173408
申请日：2018-10-29
Applicant: Palantir Technologies Inc.
Inventor： Nicholas White , Eli Bingham , Engin Ural , Jasjit Grewal
IPC: G06F16/20 , G06F16/9535 , G06F16/242 , G06F16/34 , G06F16/2457
Abstract: According to certain aspects, a computer system may be configured to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources, each of which can include various types of data, including email data, system logon data, system logoff data, badge swipe data, employee data, job processing data, etc. associated with a plurality of individuals. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system can resolve the data from each of the plurality of data sources to unique individuals of the plurality of individuals. The system can also determine an efficiency indicator based at least in part on a comparison of individuals of the unique individuals that have at least one common characteristic.
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公开(公告)号：US10423582B2
公开(公告)日：2019-09-24
申请号：US15824096
申请日：2017-11-28
Applicant: Palantir Technologies, Inc.
Inventor： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
IPC: G06F16/174 , G06F16/10 , G06F16/13 , G06F16/17 , G06F16/35 , G06F16/14 , G06F16/248 , G06F16/25 , G06F16/901 , G06F16/23 , G06F16/9535 , G06F16/2457 , G06F17/00 , G06F11/20
Abstract: A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
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Patent Agency Ranking
公开(公告)号：US10127289B2
公开(公告)日：2018-11-13
申请号：US15233149
申请日：2016-08-10
Applicant: Palantir Technologies Inc.
Inventor： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC: G06F17/30
Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
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公开(公告)号：US09639578B2
公开(公告)日：2017-05-02
申请号：US14961830
申请日：2015-12-07
Applicant: PALANTIR TECHNOLOGIES, INC.
Inventor： Geoffrey Stowe , Chris Fischer , Paul George , Eli Bingham , Rosco Hill
CPC classification number: G06F17/30153 , G06F11/2025 , G06F17/00 , G06F17/30067 , G06F17/30091 , G06F17/30106 , G06F17/30129 , G06F17/30371 , G06F17/30528 , G06F17/30554 , G06F17/30569 , G06F17/30705 , G06F17/30867 , G06F17/30955
Abstract: A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.
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18.发明公开公开(公告)号：US20230297582A1
公开(公告)日：2023-09-21
申请号：US18325616
申请日：2023-05-30
Applicant: Palantir Technologies Inc.
Inventor： Lawrence Manning , Rahul Mehta , Daniel Erenrich , Guillem Palou Visa , Roger Hu , Xavier Falco , Rowan Gilmore , Eli Bingham , Jason Prestinario , Yifei Huang , Daniel Fernandez , Jeremy Elser , Clayton Sader , Rahul Agarwal , Matthew Elkherj , Nicholas Latourette , Aleksandr Zamoshchin
IPC: G06F16/2457 , G06F16/35 , G06F16/9535 , G06F16/28 , G06F18/23
CPC classification number: G06F16/24578 , G06F16/35 , G06F16/9535 , G06F16/285 , G06F18/23
Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
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公开(公告)号：US10198515B1
公开(公告)日：2019-02-05
申请号：US14816599
申请日：2015-08-03
Applicant: Palantir Technologies Inc.
Inventor： Nicholas White , Eli Bingham , Engin Ural , Jasjit Grewal
IPC: G06F17/30
Abstract: According to certain aspects, a computer system may be configured to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources, each of which can include various types of data, including email data, system logon data, system logoff data, badge swipe data, employee data, job processing data, etc. associated with a plurality of individuals. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system can resolve the data from each of the plurality of data sources to unique individuals of the plurality of individuals. The system can also determine an efficiency indicator based at least in part on a comparison of individuals of the unique individuals that have at least one common characteristic.
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公开(公告)号：US20180322175A1
公开(公告)日：2018-11-08
申请号：US16023251
申请日：2018-06-29
Applicant: Palantir Technologies Inc.
Inventor： Feridun Arda Kara , Eli Bingham , John Garrod , Daniel Erenrich , Anirvan Mukherjee , Ted Mabrey , Andrew Ash , Zachary Bush , Allen Cai , Winnie Chai , Greg Cohan , Chris Dorsey , William Dwyer , Gilad Gray , Sean Kelley , Dennis Kwon , Chris Lewis , Greg Martin , Parvathy Menon , Brian Ngo , Asli Ozyar , Mike Reilly , Jacob Scott , Ankit Shankar , Matt Sills , Spencer Stamats , Geoff Stowe , Samir Talwar , Engin Ural , Patricio Jose Velez , Holt Wilkins , Diane Wu , Drausin Wulsin , Di Wu , Yu-hsin Joyce Chen , Baris Kaya
CPC classification number: G06F17/30554 , G06F17/30572 , G06F17/30598 , G06Q10/0639
Abstract: Systems and methods are provided for analyzing entity performance. In one implementation, a method is provided that includes recognizing an identifier associated with an entity and accessing a data structure comprising information associated with a plurality of interactions. The method also comprises identifying one or more interactions of the plurality of interactions based on the recognized identifier. The method further comprises processing the information of the identified interactions to analyze a performance of the entity and providing the processed information to display the performance of the entity on a user interface.
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