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    DATA ANALYTIC SYSTEMS
    61.
    发明公开
    DATA ANALYTIC SYSTEMS 审中-公开

    公开(公告)号：US20240086376A1

    公开(公告)日：2024-03-14

    申请号：US18488826

    申请日：2023-10-17

    Applicant: Palantir Technologies Inc.

    Inventor： PATRICK KOENIG ,  PAUL NEPYWODA ,  ROBERT FINK

    IPC: G06F16/21 ,  G06F16/23 ,  G06F16/2453 ,  G06F16/2455 ,  G06F16/25

    CPC classification number: G06F16/211 ,  G06F16/2365 ,  G06F16/24532 ,  G06F16/2455 ,  G06F16/254

    Abstract: A method comprises receiving, at a build service of a build server, an external dataset and an adaptor application module, the external dataset being in a specific format, the adaptor application module providing information relevant to a build pipeline maintained by the build service for building an output dataset based on the external dataset, the information including changes to the external dataset since a previous build of the output dataset is performed and a data schema used in the previous build, the build pipeline involving data only in one or more formats other than the specific format; incorporating the external dataset into the build pipeline without the external dataset being reformatted in accordance with requirements of the build service; receiving a request from the adaptor application module for specific information relating to a most recent data build run by the build service; providing a response to the adaptor application module.

    Systems and methods for implementing a machine learning approach to modeling entity behavior
    62.
    发明授权
    Systems and methods for implementing a machine learning approach to modeling entity behavior 有权

    公开(公告)号：US11928211B2

    公开(公告)日：2024-03-12

    申请号：US17991119

    申请日：2022-11-21

    Applicant: Palantir Technologies Inc.

    Inventor： Paul Gribelyuk ,  Han Xu ,  Kelvin Lau ,  Pierre Cholet

    IPC: G06F21/55 ,  G06F16/901 ,  G06N20/00

    CPC classification number: G06F21/554 ,  G06F16/9024 ,  G06F21/552 ,  G06N20/00

    Abstract: Systems and methods are provided for implementing a machine learning approach to modeling entity behavior. Fixed information and periodically updated information may be utilized to predict the behavior of an entity. By incorporating periodically updated information, the system is able to maintain an up-to-date prediction of each entity's behavior, while also accounting for entity action with respect to ongoing obligations. The system may generate behavior scores for the set of entities. In some embodiments, the behavior scores that are generated may indicate the transactional risk associated with each entity. Using the behavior scores generated, a user may be able to assess the credit riskiness of individual entities and instruct one or more individuals assigned to the entities to take one or more actions based on the credit riskiness of the individual entities.

    SYSTEMS AND METHODS FOR GENERATING INTERRELATED NOTIONAL DATA
    64.
    发明公开
    SYSTEMS AND METHODS FOR GENERATING INTERRELATED NOTIONAL DATA 审中-公开

    公开(公告)号：US20240070141A1

    公开(公告)日：2024-02-29

    申请号：US18239471

    申请日：2023-08-29

    Applicant: Palantir Technologies Inc.

    Inventor： Hannah Cohen ,  Myles Novick ,  Timothy Schwab

    IPC: G06F16/23 ,  G06F16/21 ,  G06F21/60

    CPC classification number: G06F16/2365 ,  G06F16/213 ,  G06F21/60

    Abstract: Disclosed herein are systems and methods for generating notional data. The method includes: receiving seed data of one or more object types in a base dataframe; defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types; generating data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships; and generating the notional data based at least in part on the generated data of the one or more object types.

    Inferring a dataset schema from input files
    69.
    发明授权
    Inferring a dataset schema from input files 有权

    公开(公告)号：US11907181B2

    公开(公告)日：2024-02-20

    申请号：US16748351

    申请日：2020-01-21

    Applicant: Palantir Technologies Inc.

    Inventor： Nir Ackner ,  Eric Lin

    IPC: G06F16/21 ,  G06F3/06 ,  G06F40/205

    CPC classification number: G06F16/211 ,  G06F3/0638 ,  G06F40/205

    Abstract: Techniques for generating a schema for a data input file are described herein. In an embodiment, a server computer receives a data input file. The server computer system selects a sample excerpt from the data input which comprises a subset of the data input file. The server computer system analyzes the sample excerpt to determine a row delimiter for the data input file, a column delimiter for the data input file, and a plurality of data format types. Using the column delimiter, row delimiter, and plurality of data format types, the server computer system generates a candidate schema for the data input file.

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