Relation-enhancement knowledge graph embedding method and system

    公开(公告)号:US11797507B2

    公开(公告)日:2023-10-24

    申请号:US17821633

    申请日:2022-08-23

    CPC classification number: G06F16/2228 G06F16/288 G06F40/30

    Abstract: The present invention relates to a relation-enhancement knowledge graph embedding method and system, wherein the method at least comprises: performing collaborative coordinate-transformation on entities in the knowledge graph; performing relation core enhancement by means of relation-entropy weighting, so as to endow entity vectors with strong relation property; building an interpretability mechanism for a knowledge graph embedding model, and accounting for effectiveness and feasibility of the relation enhancement by proving convergence of the knowledge graph embedding model; and using a dynamic parameter-adjusting strategy to perform learn representation learning of to the vectors in the knowledge graph, and configuring deviation control to ensure accurate embedding. The present invention can measure rationality of facts with improved accuracy, prove through reasoning the modeling ability of the model from the perspective of complex relation pairs, perform vector computing for entities and relations, thereby accomplishes knowledge graph embedding and reasoning.

    Method and system for ensuring search completeness of searchable public key encryption

    公开(公告)号:US11770250B2

    公开(公告)日:2023-09-26

    申请号:US17444224

    申请日:2021-08-02

    CPC classification number: H04L9/30 H04L9/0618 H04L9/50

    Abstract: The present invention relates a method for ensuring search completeness of searchable public key encryption, applicable to a blockchain network formed by a plurality of computer nodes. The method at least comprises: the blockchain network receiving a keyword ciphertext and a corresponding file-identifier ciphertext generated by a transmitting end based on the public key encryption, and at least one miner storing the ciphertexts in a ciphertext table; the blockchain network receiving a search trapdoor Tw transmitted by a receiving end, generated according to a private key and a keyword w to be searched; the at least one miner in the blockchain network performing a secure search based on information of a state table and the search trapdoor Tw, and outputting a search result to the blockchain network; and the blockchain network feeding the search result back to the receiving end. The invention uses the blockchain technology to solve the long-standing search completeness problem in searchable public key encryption, and the proposed method has universality.

    NETWORK TRANSMISSION OPTIMIZATION DEVICE FOR GRAPH-TYPE BLOCKCHAIN AND METHOD THEREOF

    公开(公告)号:US20230130074A1

    公开(公告)日:2023-04-27

    申请号:US17806646

    申请日:2022-06-13

    Abstract: The present invention relates to a network transmission optimization device for a graph-type blockchain, at least comprising a transaction processing module, a node managing module, and a route managing module, wherein the transaction processing module performs compression on a transaction, and transaction data obtained through the compression are transmitted among different clusters through a routing node selected by the route managing module from at least one cluster, wherein the at least one cluster is obtained through dividing plural nodes by the node managing module. The network transmission optimization method provides a transaction coding scheme to the existing graph-type blockchain systems, and improve use efficiency of network bandwidth by means of parallelized broadcast. The structured network topology of the network transmission optimization method is made to address delay among nodes, and is adaptive to dynamic joining and exit of nodes, thereby improving network transmission efficiency.

    Tensor-based optimization method for memory management of a deep-learning GPU and system thereof

    公开(公告)号:US11625320B2

    公开(公告)日:2023-04-11

    申请号:US16946690

    申请日:2020-07-01

    Abstract: The present disclosure relates to a tensor-based optimization method for GPU memory management of deep learning, at least comprising steps of: executing at least one computing operation, which gets tensors as input and generates tensors as output; when one said computing operation is executed, tracking access information of the tensors, and setting up a memory management optimization decision based on the access information, during a first iteration of training, performing memory swapping operations passively between a CPU memory and a GPU memory so as to obtain the access information about the tensors regarding a complete iteration; according to the obtained access information about the tensors regarding the complete iteration, setting up a memory management optimization decision; and in a successive iteration, dynamically adjusting the set optimization decision of memory management according to operational feedbacks.

    Container-based network functions virtualization platform

    公开(公告)号:US11563689B2

    公开(公告)日:2023-01-24

    申请号:US17248519

    申请日:2021-01-28

    Abstract: The present invention relates to a container-based network function virtualization (NFV) platform, comprising at least one master node and at least one slave node, the master node is configured to, based on interference awareness, assign container-based network functions (NFs) in a master-slave-model-based, distributed computing system that has at least two slave nodes to each said slave node in a manner that relations among characteristics of the to-be-assigned NFs, info of load flows of the to-be-assigned NFs, communication overheads between the individual slave nodes, processing performance inside individual slave nodes, and load statuses inside individual said slave nodes are measured.

    DEEP-LEARNING BASED DEVICE AND METHOD FOR DETECTING SOURCE-CODE VULNERABILITY WITH IMPROVED ROBUSTNESS

    公开(公告)号:US20220292200A1

    公开(公告)日:2022-09-15

    申请号:US17444612

    申请日:2021-08-06

    Abstract: The present invention relates a device for improving robustness of deep-learning based detection of source-code vulnerability, the device at least comprises a code-converting module, a mapping module, and a neural-network module, wherein the mapping module is in data connection with the code-converting module, the mapping module is in data connection with the neural-network module, respectively, and the neural-network module includes at least two first classifiers, based on a received first training program source code, the mapping module maps a plurality of code snippets, and the neural-network module trains the at least two first classifiers according to a first sample vector. The present invention improves the robustness of detection of source-code vulnerability by performing classification training on the feature generators and the classifiers.

    Live page migration for hybrid memory virtual machines

    公开(公告)号:US10810037B1

    公开(公告)日:2020-10-20

    申请号:US16774047

    申请日:2020-01-28

    Abstract: The present invention relates to a hybrid memory system with live page migration for virtual machine, and the system comprises a physical machine installed with a virtual machine and being configured to: build a channel for a shared memory between the virtual machine and a hypervisor; make the hypervisor generate to-be-migrated cold/hot page information and writing write the to-be-migrated cold/hot page information into the shared memory; make the virtual machine read the to-be-migrated cold/hot page information from the shared memory; and make the virtual machine according to the read to-be-migrated cold/hot page information perform a page migration process across heterogeneous memories of the virtual machine without stopping the virtual machine.

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