公开(公告)号：US20180081896A1

公开(公告)日：2018-03-22

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: G06F17/30 ,  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.

公开(公告)号：US09727622B2

公开(公告)日：2017-08-08

申请号：US14306154

申请日：2014-06-16

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 ,  PJ Valez ,  Holt Wilkins ,  Diane Wu ,  Drausin Wulsin ,  Di Wu ,  Joyce Yu-Hsin Chen ,  Bar Kaya

IPC: G06F17/30 ,  G06Q10/06

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 accessing a data structure comprising a plurality of interactions associated with multiple entities. The method also includes evaluating one or more interactions of the plurality of interactions associated with a consuming entity of the multiple entities. The method further includes determining whether the one or more interactions associated with the consuming entity comprise an identified location information of the consuming entity.

公开(公告)号：US20170052958A1

公开(公告)日：2017-02-23

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

CPC classification number: G06F17/3053 ,  G06F17/30705 ,  G06F17/30867

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.

Abstract translation: 公开了计算机实现的系统和方法，用于自动聚类和规范地识别各种数据结构中的相关数据。 数据结构可以包括多个记录，其中每个记录与相应实体相关联。 根据一些实施例，系统和方法还包括通过将记录分组成对来识别与相应实体相关联的记录簇，分析相应的对以确定该对的两个成员与公共实体相关联的概率，以及识别 一组重叠的对以生成与公共实体相关的记录集合。 可以通过分析记录字段并识别相似性来进一步分析集群以确定相应实体的规范名称或其他属性。