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公开(公告)号：US11636123B2
公开(公告)日：2023-04-25
申请号：US16223602
申请日：2018-12-18
发明人： Freddy Lecue , Chahrazed Bouhini , Jeremiah Hayes , Mykhaylo Zayats , Nicholas McCarthy , Qurrat Ul Ain
IPC分类号： G06F16/2458 , G06F16/23 , G06F16/901 , G06F17/11
摘要： Knowledge graph systems are disclosed for enhancing a knowledge graph by generating a new node. The knowledge graph system converts a knowledge graph into an embedding space, and selects a region of interest from within the embedding space. The knowledge graph system further identifies, from the region of interest, one or more gap regions, and calculates a center for each gap region. A node is generated for each gap region, and the information represented by the node is added to the original knowledge graph to generate an updated knowledge graph.
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公开(公告)号：US12051010B2
公开(公告)日：2024-07-30
申请号：US16560499
申请日：2019-09-04
发明人： Luca Costabello , Mykhaylo Zayats , Jeremiah Hayes
摘要： Complex computer system architectures are described for analyzing data elements of a knowledge graph, and predicting new surprising or unforeseen facts from relational learning applied to the knowledge graph. This discovery process takes advantage of the knowledge graph structure to improve the computing capabilities of a device executing a discovery calculation by applying both training and inference analysis techniques on the knowledge graph within an embedding space, and generating a scoring strategy for predicting surprising facts that may be discoverable from the knowledge graph.
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公开(公告)号：US11789991B2
公开(公告)日：2023-10-17
申请号：US16256424
申请日：2019-01-24
发明人： Freddy Lecue , Chahrazed Bouhini , Jeremiah Hayes , Mykhaylo Zayats , Nicholas McCarthy , Qurrat Ul Ain
IPC分类号： G06N5/02 , G06F16/36 , G06F17/11 , G06F16/2457 , G06F18/22 , G06F18/213
CPC分类号： G06F16/36 , G06F16/2457 , G06F17/11 , G06F18/213 , G06F18/22 , G06N5/02
摘要： Complex computer system architectures are described for utilizing a knowledge data graph comprised of elements, and selecting a discovery element to replace an existing element of a formulation depicted in the knowledge data graph. The substitution process takes advantage of the knowledge data graph structure to improve the computing capabilities of a computing device executing a substitution calculation by translating the knowledge data graph into an embedding space, and determining a discovery element from within the embedding space.
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公开(公告)号：US20200242484A1
公开(公告)日：2020-07-30
申请号：US16256424
申请日：2019-01-24
发明人： Freddy Lecue , Chahrazed Bouhini , Jeremiah Hayes , Mykhaylo Zayats , Nicholas McCarthy , Qurrat Ul Ain
IPC分类号： G06N5/02 , G06K9/62 , G06F16/2457 , G06F17/11
摘要： Complex computer system architectures are described for utilizing a knowledge data graph comprised of elements, and selecting a discovery element to replace an existing element of a formulation depicted in the knowledge data graph. The substitution process takes advantage of the knowledge data graph structure to improve the computing capabilities of a computing device executing a substitution calculation by translating the knowledge data graph into an embedding space, and determining a discovery element from within the embedding space.
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公开(公告)号：US11354608B2
公开(公告)日：2022-06-07
申请号：US15999019
申请日：2018-08-20
发明人： Ajitesh Prakash , Jitesh Goyal , Eilís Delany , Mykhaylo Zayats , John Emmett Mannion , Yvonne M. Browne
摘要： A device may receive organization data defining first capabilities of an organization and industry trend data that is relevant to the organization. The industry trend data may define second capabilities that are relevant to the organization. The device may provide, as input to a capability model, the organization data and the industry trend data. The capability model may have been trained to produce, as output, data specifying recommended changes for the organization. The device may determine, based on the output of the capability model and the industry trend data, a recommendation. The device may perform an action based on the recommendation.
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公开(公告)号：US20200057976A1
公开(公告)日：2020-02-20
申请号：US15999019
申请日：2018-08-20
发明人： Ajitesh Prakash , Jitesh Goyal , Eilís Delany , Mykhaylo Zayats , John Emmett Mannion , Yvonne M. Browne
摘要： A device may receive organization data defining first capabilities of an organization and industry trend data that is relevant to the organization. The industry trend data may define second capabilities that are relevant to the organization. The device may provide, as input to a capability model, the organization data and the industry trend data. The capability model may have been trained to produce, as output, data specifying recommended changes for the organization. The device may determine, based on the output of the capability model and the industry trend data, a recommendation. The device may perform an action based on the recommendation.
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公开(公告)号：US11687848B2
公开(公告)日：2023-06-27
申请号：US16385690
申请日：2019-04-16
IPC分类号： G06F16/35 , G06Q10/0631 , G06F40/30 , G06F40/44 , G06F40/295 , G06F16/36 , G06F18/214 , G06F18/231 , G06N3/045 , G06F40/284
CPC分类号： G06Q10/06311 , G06F16/355 , G06F16/36 , G06F18/214 , G06F18/231 , G06F40/295 , G06F40/30 , G06F40/44 , G06N3/045 , G06F40/284
摘要： A device receives a request associated with standardizing organization-specific roles within an organization, where the request includes data that identifies titles for the organization-specific roles. The device converts the data to vectors that represent semantic meanings of the titles. The device sets a configuration of a data model by assigning weighted values to title-class identifiers that are used to associate titles, of a standardized set of titles, to a hierarchy of role classifications. The device uses the data model to determine scores that indicate likelihoods of the titles mapping to the title-class identifiers. The device identifies, based on scores, a subset of title-class identifiers that associate particular titles, of the standardized set of titles, and particular role classifications. The subset of title-class identifiers is stored in association with information relating to the particular titles. The device performs an action based on the information relating to the particular titles.
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公开(公告)号：US11526849B2
公开(公告)日：2022-12-13
申请号：US16376675
申请日：2019-04-05
摘要： A device may determine an association between a second set of parameters and a third set of parameters using a pseudoinversion network and a multiple regression procedure. The device may determine semantic embeddings based on a set of semantic descriptions of the second set of parameters. The device may determine a semantic similarity between parameters of the second set of parameters based on the semantic embeddings. The device may determine a consistency error based on the semantic similarity. The device may generate, using a regression-based learning model technique, a matrix representing an association between the second set of parameters and the third set of parameters based on the association and the consistency error. The device may perform an action based on the matrix.
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