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11.发明申请公开(公告)号：US20190079937A1
公开(公告)日：2019-03-14
申请号：US16189040
申请日：2018-11-13
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：US12056718B2
公开(公告)日：2024-08-06
申请号：US16850961
申请日：2020-04-16
Applicant: Palantir Technologies Inc.
Inventor： Rahul Agarwal , Diane Wu
IPC: G06Q30/018 , G06N20/00 , G16H10/60
CPC classification number: G06Q30/0185 , G06N20/00 , G16H10/60
Abstract: Systems and methods are described for automatically processing data stored in one or more databases using machine learning to detect entities (such as health care providers, health care plan members, patients, pharmacies, and so forth) associated with health care claims that are suspected of fraudulent, wasteful, and/or abusive activity. The techniques may further or alternatively involve generating and presenting, for a set of suspected entities, natural language explanatory information explaining how and/or why each of the respective suspected entities is considered to be suspected of fraudulent, wasteful, and/or abusive activity. Feedback provided by fraud analysts and/or other subject matter experts in the misuse detection space is used to facilitate misuse detection and misuse detection presentation.
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公开(公告)号：US11704325B2
公开(公告)日：2023-07-18
申请号：US17812984
申请日：2022-07-15
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: G06F16/00 , G06F16/2457 , G06F16/35 , G06F16/9535 , G06F16/28 , G06F18/23
CPC classification number: G06F16/24578 , G06F16/285 , G06F16/35 , G06F16/9535 , 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：US11030581B2
公开(公告)日：2021-06-08
申请号：US16457348
申请日：2019-06-28
Applicant: Palantir Technologies Inc.
Inventor： Gokul Subramanian , Rahul Agarwal , William Seaton , Diane Wu
Abstract: In an embodiment, a computer-implemented method comprises, in response to receiving lead data identifying an entity associated with a health care claim relating to suspected fraud, determining one or more data sources that were used to identify the entity or the suspected fraud; determining a subset of a plurality of data display elements, based on the determined one or more data sources, wherein each of the plurality of data display elements is configured to cause displaying health care claims data associated with the entity in a designated format; automatically obtaining, from a data repository, specific health care claims data associated with the entity for each of the plurality of data display elements in the subset; generating a lead summary report associated with the entity using a report template, the subset, and the obtained specific health care claims data.
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公开(公告)号：US20240152490A1
公开(公告)日：2024-05-09
申请号：US18415253
申请日：2024-01-17
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshchin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/18 , G06F16/13 , G06F16/188 , G06F30/00 , G06N7/00
CPC classification number: G06F16/1873 , G06F16/13 , G06F16/196 , G06F30/00 , G06N7/00 , G06F2111/20
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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Patent Agency Ranking
公开(公告)号：US11907175B2
公开(公告)日：2024-02-20
申请号：US18051035
申请日：2022-10-31
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshchin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/00 , G06F16/18 , G06N7/00 , G06F16/13 , G06F16/188 , G06F30/00 , G06F111/20
CPC classification number: G06F16/1873 , G06F16/13 , G06F16/196 , G06F30/00 , G06N7/00 , G06F2111/20
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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17.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：US11488058B2
公开(公告)日：2022-11-01
申请号：US16426865
申请日：2019-05-30
Applicant: Palantir Technologies Inc.
Inventor： Rahul Agarwal , Daniel Erenrich
Abstract: In various example embodiments, a vector modeling system is configured to access a set of data distributed across client devices and stored in a structured format. The vector modeling system determines vector parameters and vector templates suitable for the set of data and transforms the set of data from the structured format into a second format including one or more vectors based on one or more transformation strategies. The vector modeling system stores the transformed data and performs machine learning analysis on the vector.
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公开(公告)号：US20210056083A1
公开(公告)日：2021-02-25
申请号：US17093381
申请日：2020-11-09
Applicant: Palantir Technologies Inc.
Inventor： David Lisuk , Daniel Erenrich , Guodong Xu , Luis Voloch , Rahul Agarwal , Simon Slowik , Aleksandr Zamoshchin , Andre Frederico Cavalheiro Menck , Anirvan Mukherjee , Daniel Chin
IPC: G06F16/18 , G06N7/00 , G06F16/13 , G06F30/00 , G06F16/188
Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
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公开(公告)号：US20200242626A1
公开(公告)日：2020-07-30
申请号：US16850961
申请日：2020-04-16
Applicant: Palantir Technologies Inc.
Inventor： Rahul Agarwal , Diane Wu
Abstract: Systems and methods are described for automatically processing data stored in one or more databases using machine learning to detect entities (such as health care providers, health care plan members, patients, pharmacies, and so forth) associated with health care claims that are suspected of fraudulent, wasteful, and/or abusive activity. The techniques may further or alternatively involve generating and presenting, for a set of suspected entities, natural language explanatory information explaining how and/or why each of the respective suspected entities is considered to be suspected of fraudulent, wasteful, and/or abusive activity. Feedback provided by fraud analysts and/or other subject matter experts in the misuse detection space is used to facilitate misuse detection and misuse detection presentation.
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