公开(公告)号：US20240037096A1

公开(公告)日：2024-02-01

申请号：US18482756

申请日：2023-10-06

申请人： Google LLC

发明人： Jeremiah Harmsen ,  Tushar Deepak Chandra ,  Marcus Fontoura

IPC分类号： G06F16/245 ,  G06N20/00 ,  G06F16/22 ,  G06N5/025 ,  G06F16/31

CPC分类号： G06F16/245 ,  G06N20/00 ,  G06F16/2228 ,  G06N5/025 ,  G06F16/319

摘要： Systems and techniques are disclosed for generating entries for a searchable index based on rules generated by one or more machine-learned models. The index entries can include one or more tokens correlated with an outcome and an outcome probability. A subset of tokens can be identified based on the characteristics of an event. The index may be searched for outcomes and their respective probabilities that correspond to tokens that are similar to or match the subset of tokens based on the event.

公开(公告)号：US11888949B2

公开(公告)日：2024-01-30

申请号：US17102387

申请日：2020-11-23

申请人： People.ai, Inc.

发明人： Oleg Rogynskyy ,  Yurii Brunets ,  Stefan Hermanek ,  Dylan Halladay

IPC分类号： G06F16/9035 ,  H04L67/50 ,  G06F16/335 ,  G06F16/2455 ,  G06F16/28 ,  G06F16/26 ,  G06F16/901 ,  G06F16/903 ,  G16H50/20 ,  G06F16/27 ,  G06F16/22 ,  G06F16/23 ,  G06F16/245 ,  G06F16/906 ,  G06F16/21 ,  G06F16/11 ,  G06F16/215 ,  G06F16/2458 ,  G06F16/25 ,  G06F16/2457 ,  G06F16/9535 ,  G06F16/178 ,  G06F16/17 ,  G06F16/29 ,  G06F16/35 ,  G06F40/295 ,  G06F7/14 ,  G06F11/30 ,  G06F11/34 ,  G06F21/62 ,  G06N3/08 ,  G06N5/04 ,  G06N7/02 ,  G06Q10/04 ,  G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/107 ,  G06Q10/1091 ,  G06Q10/1093 ,  G06Q50/22 ,  H04L41/14 ,  H04L43/026 ,  H04L43/045 ,  H04L43/062 ,  H04L43/065 ,  H04L43/067 ,  H04L43/0876 ,  H04L43/00 ,  H04L51/046 ,  H04L67/125 ,  H04L67/30 ,  H04L67/306 ,  H04M3/436 ,  H04M15/00 ,  G06F40/237 ,  H04L67/303 ,  G06N5/025 ,  G06F16/31 ,  G06F16/182 ,  G06F40/20 ,  H04L51/42 ,  H04L51/212 ,  H04L51/234 ,  H04L61/45 ,  G06Q10/109 ,  G06F9/54 ,  G16H15/00 ,  G16H50/30 ,  G06N20/00 ,  G06F40/205 ,  G06Q10/10 ,  H04M3/56 ,  H04L12/14 ,  H04L101/37 ,  H04L101/00 ,  H04M3/22 ,  H04L101/35

CPC分类号： H04L67/535 ,  G06F7/14 ,  G06F9/542 ,  G06F11/3024 ,  G06F11/3452 ,  G06F11/3495 ,  G06F16/122 ,  G06F16/178 ,  G06F16/1734 ,  G06F16/182 ,  G06F16/212 ,  G06F16/215 ,  G06F16/219 ,  G06F16/22 ,  G06F16/221 ,  G06F16/2228 ,  G06F16/2264 ,  G06F16/2272 ,  G06F16/23 ,  G06F16/235 ,  G06F16/2358 ,  G06F16/2365 ,  G06F16/2379 ,  G06F16/2386 ,  G06F16/245 ,  G06F16/2457 ,  G06F16/2477 ,  G06F16/24558 ,  G06F16/24564 ,  G06F16/24575 ,  G06F16/24578 ,  G06F16/254 ,  G06F16/256 ,  G06F16/26 ,  G06F16/27 ,  G06F16/273 ,  G06F16/28 ,  G06F16/285 ,  G06F16/288 ,  G06F16/289 ,  G06F16/29 ,  G06F16/313 ,  G06F16/337 ,  G06F16/355 ,  G06F16/901 ,  G06F16/906 ,  G06F16/9024 ,  G06F16/9035 ,  G06F16/90344 ,  G06F16/9535 ,  G06F21/6218 ,  G06F21/6245 ,  G06F40/20 ,  G06F40/237 ,  G06F40/295 ,  G06N3/08 ,  G06N5/025 ,  G06N5/04 ,  G06N7/02 ,  G06Q10/04 ,  G06Q10/06312 ,  G06Q10/06315 ,  G06Q10/06393 ,  G06Q10/06398 ,  G06Q10/063114 ,  G06Q10/107 ,  G06Q10/109 ,  G06Q10/1091 ,  G06Q10/1095 ,  G06Q50/22 ,  G16H50/20 ,  H04L41/14 ,  H04L43/026 ,  H04L43/045 ,  H04L43/062 ,  H04L43/065 ,  H04L43/067 ,  H04L43/0876 ,  H04L43/14 ,  H04L51/046 ,  H04L51/212 ,  H04L51/234 ,  H04L51/42 ,  H04L61/45 ,  H04L67/125 ,  H04L67/30 ,  H04L67/303 ,  H04L67/306 ,  H04M3/436 ,  H04M15/755 ,  G06F40/205 ,  G06N20/00 ,  G06Q10/10 ,  G16H15/00 ,  G16H50/30 ,  H04L12/1407 ,  H04L2101/00 ,  H04L2101/35 ,  H04L2101/37 ,  H04M3/2218 ,  H04M3/56

摘要： The present disclosure relates to systems and methods for determining an engagement profile of a participant by associating electronic activities to a profile. It may generate the engagement profile based on analysis of the electronic activity level. An example implementation may contain the following steps. The system may access for a first record object a plurality of electronic activities linked with the first record object. The system may identify for a participant from the plurality of electronic activities a set of electronic activities including the participant. The system may determine an engagement profile of the participant based on a first number of electronic activities of the set of electronic activities sent by the participant, a second number of the set of electronic activities received by the participant and a temporal distribution of the set of electronic activities. The system may store the engagement profile in one or more data structures.

公开(公告)号：US11887712B2

公开(公告)日：2024-01-30

申请号：US17120054

申请日：2020-12-11

申请人： MEDTRONIC MINIMED, INC.

发明人： Anirban Roy ,  Benyamin Grosman

IPC分类号： G16H20/17 ,  G16H20/10 ,  G16H50/50 ,  G16H40/67 ,  G16H10/40 ,  G16H20/60 ,  G06F16/23 ,  G06F16/245 ,  A61B5/11 ,  A61B5/145 ,  A61B5/00 ,  A61M5/172 ,  G16H20/30 ,  G06F18/214 ,  G06N7/01 ,  G06V10/80 ,  G06V40/20

CPC分类号： G16H20/10 ,  A61B5/1118 ,  A61B5/14532 ,  A61B5/4866 ,  A61B5/7267 ,  A61B5/7278 ,  A61B5/7282 ,  A61M5/1723 ,  G06F16/2379 ,  G06F16/245 ,  G06F18/214 ,  G06F18/2148 ,  G06N7/01 ,  G06V10/809 ,  G16H10/40 ,  G16H20/17 ,  G16H20/30 ,  G16H20/60 ,  G16H40/67 ,  G16H50/50 ,  G06V40/20

摘要： Technologies are provided for classifying detected events as labeled event combinations. Input data for different combinations of detected events are received at a server system, and each combination of detected events is processed at the server system. Processing can include classifying that combination of detected events at a classifier to map that combination of detected events to a probability of an increased insulin delivery demand or a probability of a decreased insulin delivery demand, and labeling each classified combination of detected events with a label to generate a corresponding labeled event combination that has the probability of the increased insulin delivery demand or the probability of the decreased insulin delivery demand. Each labeled event combination can be stored in storage as a database of labeled event combinations, and selected ones of the labeled event combinations can be processed at a client application to generate an output result.

公开(公告)号：US11886422B1

公开(公告)日：2024-01-30

申请号：US17216347

申请日：2021-03-29

申请人： Amazon Technologies, Inc.

发明人： Bohou Li ,  Vijayan Prabhakaran ,  Mehul A. Shah ,  Benjamin Sowell ,  Douglas Brian Terry

IPC分类号： G06F16/23 ,  G06F16/245 ,  G06F16/21 ,  G06F16/22

CPC分类号： G06F16/2379 ,  G06F16/219 ,  G06F16/2282 ,  G06F16/2343 ,  G06F16/245

摘要： A protocol for implementing ACID transactions that provides snapshot isolation in a distributed setting that does not require synchronized clocks is described. The protocol ensures at commit time that transactions touching common objects do not commit out of order. The protocol can be used in the context of a distributed data lake built on an object store in which clients can transactionally add or remove objects from logical tables.

公开(公告)号：US11882220B2

公开(公告)日：2024-01-23

申请号：US17733839

申请日：2022-04-29

申请人： Protegrity Corporation

发明人： David Clyde Williamson ,  George Curran ,  Raul Ortega ,  Jan Boberg ,  Rajnish Jain ,  Yigal Rozenberg

IPC分类号： H04L9/32 ,  G06F3/06 ,  H04L9/40 ,  G06F21/62 ,  H04L9/08 ,  G06F16/245

CPC分类号： H04L9/3213 ,  G06F3/067 ,  G06F3/0622 ,  G06F3/0659 ,  G06F16/245 ,  G06F21/6218 ,  G06F21/6254 ,  H04L9/0869 ,  H04L9/0894 ,  H04L63/0853 ,  H04L63/102 ,  H04L2209/08

摘要： Data can be protected in a centralized tokenization environment. A security value is received by a central server from a client device. The central server accesses a token table corresponding to the client device and generates a reshuffled static token table from the accessed token table based on the received security value. When the client device subsequently provides data to be protected to the central server, the central server tokenizes the provided data using the reshuffled static token table and stores the tokenized data in a multi-tenant database. By reshuffling token tables using security values unique to client devices, the central server can protect and store data for each of multiple tenants such that if the data of one tenant is compromised, the data of each other tenant is not compromised.

公开(公告)号：US11880360B2

公开(公告)日：2024-01-23

申请号：US17355853

申请日：2021-06-23

申请人： Opsera Inc

发明人： Ravi Kumar Chivukula ,  Chandra Ranganathan ,  Vasanthavishnu Vasudevan ,  Sundar Rajan Renganathan ,  Tejas Bharadwaj ,  Shrey Malhotra ,  Venkat Yuvraj ,  Phani Sree Harsha Pullabhatlapogada ,  Kishore Rajan

IPC分类号： G06F16/245 ,  G06F16/248 ,  G06F3/0482 ,  G06F3/0486 ,  G06F8/77 ,  G06F8/35 ,  G06F8/71 ,  G06F11/34 ,  G06Q10/0637 ,  G06F9/50 ,  G06Q10/101 ,  H04L67/133 ,  G06F8/10

CPC分类号： G06F16/245 ,  G06F3/0482 ,  G06F3/0486 ,  G06F8/10 ,  G06F8/35 ,  G06F8/71 ,  G06F8/77 ,  G06F9/5005 ,  G06F11/3438 ,  G06F16/248 ,  G06Q10/0637 ,  G06Q10/101 ,  H04L67/133

摘要： The present invention extends to methods, systems, and computer program products for deriving unified insights ad logs from DevOps Cl/CD tools and pipeline data. In general, a data transformer facilitates data normalization and serialization converting raw data across multiple DevOps tools and stores the data into a Data Lake in accordance with a customized schema. A continuous orchestrator sequences, aggregates and contextualizes the logs, providing an intuitive way of troubleshooting issues across a DevOps environment, historical data for compliance and audit purposes, and a build manifest for root cause analysis. The continuous orchestrator also processes the logs and leverages a KPI framework, providing intelligent dashboards across 90+ KPI's and a plurality of different dimensions (Planning, Development/pipelines, security, quality, operations, productivity and source code) to help customers make smart decisions and do more with less.

公开(公告)号：US11876874B2

公开(公告)日：2024-01-16

申请号：US17175982

申请日：2021-02-15

申请人： People.ai, Inc.

发明人： Oleg Rogynskyy ,  Brittney Hall ,  Dylan Halladay ,  John Wulf ,  Vardhman Jain

IPC分类号： G06F16/335 ,  G16H15/00 ,  H04L67/50 ,  G06F16/9035 ,  G06F16/2455 ,  G06F16/28 ,  G06F16/26 ,  G06F16/901 ,  G06F16/903 ,  G16H50/20 ,  G06F16/27 ,  G06F16/22 ,  G06F16/23 ,  G06F16/245 ,  G06F16/906 ,  G06F16/21 ,  G06F16/11 ,  G06F16/215 ,  G06F16/2458 ,  G06F16/25 ,  G06F16/2457 ,  G06F16/9535 ,  G06F16/178 ,  G06F16/17 ,  G06F16/29 ,  G06F16/35 ,  G06F40/295 ,  G06F7/14 ,  G06F11/30 ,  G06F11/34 ,  G06F21/62 ,  G06N3/08 ,  G06N5/04 ,  G06N7/02 ,  G06Q10/04 ,  G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/107 ,  G06Q10/1091 ,  G06Q10/1093 ,  G06Q50/22 ,  H04L41/14 ,  H04L43/026 ,  H04L43/045 ,  H04L43/062 ,  H04L43/065 ,  H04L43/067 ,  H04L43/0876 ,  H04L43/00 ,  H04L51/046 ,  H04L67/125 ,  H04L67/30 ,  H04L67/306 ,  H04M3/436 ,  H04M15/00 ,  G06F40/237 ,  H04L67/303 ,  G06N5/025 ,  G06F16/31 ,  G06F16/182 ,  G06F40/20 ,  H04L51/42 ,  H04L51/212 ,  H04L51/234 ,  H04L61/45 ,  G06Q10/109 ,  G06F9/54 ,  G16H50/30 ,  G06N20/00 ,  G06F40/205 ,  G06Q10/10 ,  H04M3/56 ,  H04L12/14 ,  H04L101/37 ,  H04L101/00 ,  H04M3/22 ,  H04L101/35

CPC分类号： H04L67/535 ,  G06F7/14 ,  G06F9/542 ,  G06F11/3024 ,  G06F11/3452 ,  G06F11/3495 ,  G06F16/122 ,  G06F16/178 ,  G06F16/1734 ,  G06F16/182 ,  G06F16/212 ,  G06F16/215 ,  G06F16/219 ,  G06F16/22 ,  G06F16/221 ,  G06F16/2228 ,  G06F16/2264 ,  G06F16/2272 ,  G06F16/23 ,  G06F16/235 ,  G06F16/2358 ,  G06F16/2365 ,  G06F16/2379 ,  G06F16/2386 ,  G06F16/245 ,  G06F16/2457 ,  G06F16/2477 ,  G06F16/24558 ,  G06F16/24564 ,  G06F16/24575 ,  G06F16/24578 ,  G06F16/254 ,  G06F16/256 ,  G06F16/26 ,  G06F16/27 ,  G06F16/273 ,  G06F16/28 ,  G06F16/285 ,  G06F16/288 ,  G06F16/289 ,  G06F16/29 ,  G06F16/313 ,  G06F16/337 ,  G06F16/355 ,  G06F16/901 ,  G06F16/906 ,  G06F16/9024 ,  G06F16/9035 ,  G06F16/90344 ,  G06F16/9535 ,  G06F21/6218 ,  G06F21/6245 ,  G06F40/20 ,  G06F40/237 ,  G06F40/295 ,  G06N3/08 ,  G06N5/025 ,  G06N5/04 ,  G06N7/02 ,  G06Q10/04 ,  G06Q10/06312 ,  G06Q10/06315 ,  G06Q10/06393 ,  G06Q10/06398 ,  G06Q10/063114 ,  G06Q10/107 ,  G06Q10/109 ,  G06Q10/1091 ,  G06Q10/1095 ,  G06Q50/22 ,  G16H50/20 ,  H04L41/14 ,  H04L43/026 ,  H04L43/045 ,  H04L43/062 ,  H04L43/065 ,  H04L43/067 ,  H04L43/0876 ,  H04L43/14 ,  H04L51/046 ,  H04L51/212 ,  H04L51/234 ,  H04L51/42 ,  H04L61/45 ,  H04L67/125 ,  H04L67/30 ,  H04L67/303 ,  H04L67/306 ,  H04M3/436 ,  H04M15/755 ,  G06F40/205 ,  G06N20/00 ,  G06Q10/10 ,  G16H15/00 ,  G16H50/30 ,  H04L12/1407 ,  H04L2101/00 ,  H04L2101/35 ,  H04L2101/37 ,  H04M3/2218 ,  H04M3/56

摘要： The present disclosure relates to systems and methods for filtering electronic activities. The method includes identifying an electronic activity. The method includes parsing the electronic activity to identify one or more electronic accounts in the electronic activity. The method includes determining, responsive to parsing the electronic activity, that the electronic activity is associated with an electronic account of the one or more electronic accounts. The method includes selecting, based on the electronic account, one or more filtering policies associated with the data source provider to apply to the electronic activity. The method includes determining, by applying the selected one or more filtering policies to the electronic activity, to restrict the electronic activity from further processing based on the electronic activity satisfying at least one of the selected one or more filtering policies. The method includes restricting, the electronic activity from further processing.

公开(公告)号：US11874834B2

公开(公告)日：2024-01-16

申请号：US17588543

申请日：2022-01-31

申请人： HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

发明人： Shine Mathew ,  Ashish Dange ,  Harsh Singh ,  Javeed Pasha

IPC分类号： G06F16/245 ,  G06F16/2453 ,  G06F16/2455

CPC分类号： G06F16/24544 ,  G06F16/2456

摘要： A process includes accessing a query that is associated with joining a fact table with a plurality of dimension tables. The fact table includes a primary key that includes a set of columns, which are covered by the dimension tables. The process includes determining a query plan for processing the query. The query plan has an associated join order. Determining the query plan includes determining a plurality of sets of the plurality of dimension tables, where each set includes dimension tables, which cover the set of columns of the primary key. Determining the query plan includes evaluating costs that are associated with joining subsets of the plurality of sets with the fact table. Based on the costs, a given subset of the plurality of subsets is selected. Determining the query plan includes constraining the join order based on the given subset so that the dimension tables of the given subset are joined before the fact table.

公开(公告)号：US11870870B2

公开(公告)日：2024-01-09

申请号：US15876065

申请日：2018-01-19

申请人： Meteor Development Group, Inc.

发明人： Nicholas Martin ,  Matthew DeBergalis ,  Geoffroy Pierre Alexis Carrier

IPC分类号： G06F16/00 ,  H04L67/568 ,  H04L9/40 ,  G06F16/245 ,  G06F16/951 ,  G06F16/242 ,  H04L67/02

CPC分类号： H04L67/568 ,  G06F16/245 ,  G06F16/2433 ,  G06F16/951 ,  H04L63/0227 ,  H04L63/0236 ,  H04L63/0281 ,  H04L63/101 ,  H04L67/02

摘要： Embodiments are disclosed of systems and/or techniques for rate-limiting query-type requests, such as including content-type requests, to computing and/or networking devices, such as, for example, servers, capable of communicating over a computing and/or communications network.

公开(公告)号：US11868911B1

公开(公告)日：2024-01-09

申请号：US16810238

申请日：2020-03-05

申请人： American Express Travel Related Services Company, Inc.

发明人： Rares Ioan Almasan ,  Andras L. Ferenczi ,  Mohammad N. Nauman ,  Swatee Singh ,  Man Chon U

IPC分类号： G06F16/23 ,  G06N5/04 ,  G06N20/00 ,  G06F16/22 ,  G06F16/245

CPC分类号： G06N5/04 ,  G06F16/2255 ,  G06F16/23 ,  G06F16/2365 ,  G06F16/2379 ,  G06F16/245 ,  G06N20/00

摘要： Disclosed are various approaches for managing the status of machine-learning models using distributed ledgers. A registration request for a machine-learning model can be received. The registration request can include a model name for the machine-learning model, a version identifier for the machine-learning model, a network address from which the machine-learning model can be retrieved, a source code hash for a source code version of the machine learning model, and a runtime hash for a binary executable version of the machine-learning model. A registration identifier can then be created based at least in part on the source code hash and the runtime hash. Subsequently, an entry in the distributed ledger can be created for the machine-learning model. The entry can include the registration identifier, the model name, the model version, the network address, the source code hash, and the runtime hash.