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公开(公告)号：US20230041338A1
公开(公告)日：2023-02-09
申请号：US17406283
申请日：2021-08-19
Applicant: EMC IP Holding Company LLC
Inventor： Wenbin Yang , Zijia Wang , Jiacheng Ni , Zhen Jia
IPC: G06F16/28 , G06F16/901 , G06N3/04
Abstract: A method for graph data processing comprises obtaining graph data which includes a plurality of nodes and data corresponding to the plurality of nodes respectively; classifying the plurality of nodes into at least one category of a plurality of categories, wherein the plurality of categories are associated with a plurality of node relationship patterns; determining, from a plurality of candidate parameter value sets of a graph convolutional network (GCN) model, parameter value subsets respectively matching at least one category, wherein the plurality of candidate parameter value sets are determined by training the GCN model respectively for the plurality of node relationship patterns; and using the parameter value subsets respectively matching the at least one category to respectively perform a graph convolution operation in the GCN model on data corresponding to the nodes classified into the at least one category to obtain a processing result for the graph data.
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公开(公告)号：US20220335307A1
公开(公告)日：2022-10-20
申请号：US17230433
申请日：2021-04-14
Applicant: EMC IP Holding Company LLC
Inventor： Zijia Wang , Victor Fong , Zhen Jia , Jiacheng Ni
IPC: G06N5/02 , G06N20/00 , G06F16/903 , G06F40/30
Abstract: Techniques for constructing and otherwise managing knowledge graphs in information processing system environments are disclosed. For example, a method comprises the following steps. The method collects data from a plurality of data sources. The method extracts structured data and unstructured data from the collected data, wherein unstructured data is extracted using an unsupervised machine learning process. The method forms a plurality of sub-graph structures comprising a sub-graph structure for each of the data sources based on at least a portion of the extracted structured data and unstructured data. The method combines the plurality of sub-graph structures to form a combined graph structure representing the collected data from the plurality of data sources. The resulting combined graph structure is a comprehensive knowledge graph.
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公开(公告)号：US20220239750A1
公开(公告)日：2022-07-28
申请号：US17185033
申请日：2021-02-25
Applicant: EMC IP Holding Company LLC
Inventor： Jiacheng Ni , Min Gong , Zijia Wang , Zhen Jia , Bin He
Abstract: The present disclosure relates to a method, a device, and a program product for managing a computer system. One method includes: receiving a service request for the computer system, the service request describing an operation state of the computer system; respectively determining similarities between the service request and multiple historical service requests performed for the computer system, the multiple historical service requests respectively describing multiple historical operation states of the computer system; and determining, in response to determining that a similarity between the service request and a historical service request among the multiple historical service requests satisfies a predetermined similarity condition, a solution for processing the service request based on a pairing of the service request with the historical service request and a historical solution for processing the historical service request. Further, a corresponding device and a corresponding program product are provided.
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公开(公告)号：US11836531B2
公开(公告)日：2023-12-05
申请号：US17178413
申请日：2021-02-18
Applicant: EMC IP Holding Company LLC
Inventor： Zhen Jia , Zijia Wang
CPC classification number: G06F9/5044 , G06N20/00
Abstract: A method includes: acquiring a set of operations to be performed on multiple computing units in the computing system; determining, based on the set of operations, the state of the multiple computing units, and an allocation model, an allocation action for allocating the set of operations to the multiple computing units and a reward for the allocation action, wherein the allocation model describes an association relationship among a set of operations, the state of multiple computing units, the allocation action for allocating the set of operations to the multiple computing units, and the reward for the allocation action; receiving an adjustment for the reward in response to determining that a match degree between the reward for the allocation action and a performance index of the computing system after the allocation action is performed satisfies a predetermined condition; and generating, based on the adjustment, training data for updating the allocation model.
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公开(公告)号：US20230129929A1
公开(公告)日：2023-04-27
申请号：US17541360
申请日：2021-12-03
Applicant: EMC IP Holding Company LLC
Inventor： Zijia Wang , Jiacheng Ni , Zhen Jia
Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for data processing. The method disclosed herein includes receiving, at an edge device, new data for training a model, the edge device having stored distilled data used to represent historical data to train the model, the historical data being stored in a remote device, and the amount of the historical data being greater than the amount of the distilled data. The method further includes training the model based on the new data and the distilled data. With the data processing solution of the present disclosure, the model can be trained at the edge device with fewer storage resources based on the distilled data, thereby achieving higher model accuracy.
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Patent Agency Ranking
公开(公告)号：US20230127126A1
公开(公告)日：2023-04-27
申请号：US17527798
申请日：2021-11-16
Applicant: EMC IP Holding Company LLC
Inventor： Zijia Wang , Jiacheng Ni , Zhen Jia
Abstract: Embodiments of the present disclosure relate to a computer-implemented method, a device, and a computer program product. The method includes extracting respective themes of a set of documents with release time within a first period; determining respective semantic information of the themes and frequencies of the themes appearing in the set of documents; and determining the number of documents associated with the themes within a second period according to a prediction model and based on the semantic information and frequencies of the themes. The second period is after the first period. Embodiments of the present disclosure can better predict the tendency of the themes appearing in the future based on the semantic information and frequencies of the themes.
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17.发明授权公开(公告)号：US11636004B1
公开(公告)日：2023-04-25
申请号：US17545258
申请日：2021-12-08
Applicant: EMC IP Holding Company LLC
Inventor： Jiacheng Ni , Min Gong , GuangZhou Zhou , Zijia Wang , Zhen Jia
IPC: G06F11/07 , G06F18/214 , G06N7/01
Abstract: Embodiments of the present disclosure include a method, an electronic device, and a computer program product for training a failure analysis model. In a method for training a failure analysis model in an illustrative embodiment, at least one set of log files including multiple preprocessed log files is obtained, the at least one set of log files including a marked failure cause of a storage system, and preprocessed log files in the multiple preprocessed log files including one or more potential failure causes of the storage system and scores associated with the potential failure causes; a failure cause of the storage system is predicted according to a failure analysis model and based on the potential failure causes and the scores in the multiple preprocessed log files; and parameters of the failure analysis model are updated based on a probability that the predicted failure cause is the marked failure cause.
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公开(公告)号：US11609936B2
公开(公告)日：2023-03-21
申请号：US17406283
申请日：2021-08-19
Applicant: EMC IP Holding Company LLC
Inventor： Wenbin Yang , Zijia Wang , Jiacheng Ni , Zhen Jia
IPC: G06F16/28 , G06N3/04 , G06F16/901
Abstract: A method for graph data processing comprises obtaining graph data which includes a plurality of nodes and data corresponding to the plurality of nodes respectively; classifying the plurality of nodes into at least one category of a plurality of categories, wherein the plurality of categories are associated with a plurality of node relationship patterns; determining, from a plurality of candidate parameter value sets of a graph convolutional network (GCN) model, parameter value subsets respectively matching at least one category, wherein the plurality of candidate parameter value sets are determined by training the GCN model respectively for the plurality of node relationship patterns; and using the parameter value subsets respectively matching the at least one category to respectively perform a graph convolution operation in the GCN model on data corresponding to the nodes classified into the at least one category to obtain a processing result for the graph data.
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19.发明申请公开(公告)号：US20230033980A1
公开(公告)日：2023-02-02
申请号：US17402803
申请日：2021-08-16
Applicant: EMC IP Holding Company LLC
Inventor： Jiacheng Ni , Jinpeng Liu , Qiang Chen , Zijia Wang , Zhen Jia
Abstract: The present disclosure relates to a method, a device, and a program product for processing sample data in an Internet of Things environment. A method in one embodiment includes: receiving features of the sample data from an encoder deployed in a remote device in the Internet of Things environment; acquiring a category probability corresponding to the sample data based on a classifier deployed in a local device in the Internet of Things environment and the features; and classifying the sample data to a predetermined category in response to determining that the category probability satisfies a first threshold condition. Further, a corresponding device and a corresponding program product are provided. With example implementations of the present disclosure, computing resources of devices in an Internet of Things environment can be fully utilized to process sample data.
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公开(公告)号：US20220245513A1
公开(公告)日：2022-08-04
申请号：US17191299
申请日：2021-03-03
Applicant: EMC IP Holding Company LLC
Inventor： Zijia Wang , Chenxi Hu , Jiacheng Ni , Zhen Jia
Abstract: Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for information processing. In an information processing method, a first network state representation and a first content request event of an emulated network are provided from an emulator to an agent for reinforcement learning, wherein the first content request event indicates that a request node in the emulated network requests target content stored in a source node. The emulator receives first action information from the agent, wherein the first action information indicates a first caching action determined by the agent, the first caching action including caching the target content in at least one caching node between the request node and the source node. The emulator collects, based on the execution of the first caching action in the emulated network, first training data for training the agent.
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