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公开(公告)号：US10349134B2
公开(公告)日：2019-07-09
申请号：US15639778
申请日：2017-06-30
发明人： Sofian Hamiti , Nut Limsopatham , Md Faisal Zaman , Freddy Lecue , Victor Oliveira Antonino , Gaurav Kaila
IPC分类号： H04N21/454 , G06F17/30 , H04N21/258 , H04N21/235 , H04N21/435
摘要： A device may receive multimedia data, metadata, and/or policy data. The device may process the policy data using a first set of techniques to determine a first set of embeddings for the policy data. The device may process the multimedia data or the metadata using a second set of techniques to determine a second set of embeddings for the multimedia data or the metadata. The device may process the first set of embeddings and the second set of embeddings using a knowledge graph to determine whether the multimedia content or the access by the user violates the policy. The device may perform an action based on a result of processing the first set of embeddings and the second set of embeddings. The action may relate to the multimedia content or the access to the multimedia content by the user.
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22.发明授权公开(公告)号：US10339420B1
公开(公告)日：2019-07-02
申请号：US16117475
申请日：2018-08-30
发明人： Freddy Lecue , Md Faisal Zaman
IPC分类号： G06K9/62 , G06N5/04 , G06N20/00 , G06F16/901
摘要： An example method described herein involves receiving a first data stream and a second data stream; determining that a plurality of entities are present in the image data of the first data stream; analyzing the first data stream to determine that an entity, of the plurality of entities, is unrecognizable in the image data of the first data stream; obtaining, by the device, a common knowledge graph associated with the first data stream and the second data stream, wherein the common knowledge graph includes information regarding the plurality of entities; annotating the common knowledge graph with first corresponding recognizable characteristics of the plurality of entities in the first data stream to generate a first annotated knowledge graph; annotating the common knowledge graph with second corresponding recognizable characteristics of the plurality of entities in the second data stream to generate a second annotated knowledge graph; determining whether the entity is recognizable based on the first annotated knowledge graph and the second annotated knowledge graph; and/or performing an action associated with the first data stream based on whether the entity is recognizable.
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公开(公告)号：US10262079B1
公开(公告)日：2019-04-16
申请号：US16141636
申请日：2018-09-25
发明人： Luca Costabello , Christophe Dominique Marie Gueret , Freddy Lecue , Jeremiah Hayes , Nicholas McCarthy
摘要： A device may receive individual information associated with individual activities of an individual, and may aggregate the individual information, based on a time period, to generate aggregated individual information. The device may identify patterns in the aggregated individual information, and may determine states for the patterns based on state information associated with activities capable of being performed by individuals. The device may generate a sequential knowledge graph based on modifying a knowledge graph with the states and adding a sequence of activities to the knowledge graph, and may determine embeddings for the individual activities based on the sequential knowledge graph. The device may determine anonymized activity signatures for the individual activities based on the embeddings, and may combine the anonymized activity signatures to generate a time-based anonymized activity signature for the individual, wherein the time-based anonymized activity signature providing information that may be utilized without divulging the individual information.
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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：US20210390431A1
公开(公告)日：2021-12-16
申请号：US17460674
申请日：2021-08-30
IPC分类号： G06N5/04 , G06N3/00 , G06F16/901
摘要： Implementations include providing, by the PKG platform, an initial knowledge graph based on user-specific data associated with a user, and a domain-specific knowledge graph, receiving, by the PKG platform, data representative of at least one answer provided from the user to a respective question, providing, by the PKG platform, an expanded knowledge graph based on the initial knowledge graph, the expanded knowledge graph including one or more nodes and respective edges based on the data, generating, by the PKG platform, a weighted knowledge graph based a groundtruth knowledge graph, and a targeted knowledge graph, the groundtruth knowledge graph including one or more true answers, and the targeted knowledge graph including the at least one answer provided from the user, and generating, by the PKG platform, the hyper-personalized knowledge graph (hpKG) based on the weighted knowledge graph, the hpKG being unique to the user within a domain.
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公开(公告)号：US11093856B2
公开(公告)日：2021-08-17
申请号：US15445282
申请日：2017-02-28
发明人： Freddy Lecue , Jiewen Wu , Ian Harris
摘要： Implementations are directed to receiving current data, processing the current data using a predictive model to provide a result, the result corresponding to a sub-model of the predictive model, determining a set of syntactically similar sub-models based on other data, providing at least one semantic model based on the sub-model of the predictive model, one or more syntactically similar sub-models of the set of syntactically similar sub-models, a domain ontology (knowledge graph), and constraints, the at least one semantic model being provided by merging nodes of the sub-model of the predictive model, and a previously determined sub-model of the predictive model using the domain ontology, a label of the domain ontology being used to label a merged node, determining an interpretation based on the at least one semantic model, the interpretation providing at least one reason for the result, and providing the interpretation.
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公开(公告)号：US11036718B2
公开(公告)日：2021-06-15
申请号：US16117128
申请日：2018-08-30
发明人： Freddy Lecue , Md Faisal Zaman
IPC分类号： G06F16/23 , G06F16/245 , G06F16/901
摘要： Implementations of the present disclosure are generally directed to linking entities in dynamic knowledge graphs, and more particularly, to linking entities in knowledge graphs based on contextual evolution in one or more dimensions.
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公开(公告)号：US10963743B2
公开(公告)日：2021-03-30
申请号：US15996073
申请日：2018-06-01
发明人： Freddy Lecue , Chahrazed Bouhini
摘要： Implementations include receiving a predicted value and confidence level from a first ML model, and determining that the confidence level is below a threshold, and in response: providing an encoding based on input data and non-textual information to the first ML model, the encoding representing characteristics of the input data relative to the predicted value, the characteristics including respective gradients of features of the input data, injecting the encoding into a textual knowledge graph that corresponds to a domain of the first ML model to provide an encoded knowledge graph, receiving supplemental data based on the encoded knowledge graph, and providing a supplemental predicted value from a second ML model based on the input data and the supplemental data, the second ML model having a higher number of features than the first ML model, and the supplemental predicted value having a supplemental confidence level that exceeds the threshold.
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公开(公告)号：US10915820B2
公开(公告)日：2021-02-09
申请号：US16059399
申请日：2018-08-09
发明人： Freddy Lecue , Md Faisal Zaman
IPC分类号： G06N5/02 , G06N20/00 , G06F16/901 , G06K9/62
摘要： An example method described herein involves receiving a data input; identifying a plurality of topics in the data input; determining an underrepresented set of data for a first set of topics of the plurality of topics based on a plurality of knowledge graphs associated with the first set of topics; calculating a score for each topic of the first set of topics based on a representative learning technique; determining that the score for a first topic of the first set of topics satisfies a threshold score; selecting a topic specific knowledge graph based on the first topic; identifying representative objects that are similar to objects of the data input based on the topic specific knowledge graph; generating representation data that is similar to the data input based on the representative objects to balance the underrepresented set of data with a set of data associated with a second set of topics of the plurality of topics; and performing an action associated with the representation data.
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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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