TRANSFER LEARNING SYSTEM AND METHOD FOR DEEP NEURAL NETWORK

    公开(公告)号:US20230259761A1

    公开(公告)日:2023-08-17

    申请号:US17938650

    申请日:2022-10-06

    CPC classification number: G06N3/08 G06N3/0454

    Abstract: Disclosed is a transfer learning system for a deep neural network. The transfer learning system includes a pre-trained model storage unit configured to store a plurality of pre-trained models that are deep neural network models learned using one or more pre-training datasets, a transfer learning data input unit configured to receive transfer learning data, a pre-trained model selecting unit configured to select a pre-trained model corresponding to the transfer learning data from among the plurality of stored pre-trained models, and a transfer learning unit configured to generate one or more transfer learning models by performing transfer learning using the selected pre-trained model and the transfer learning data.

    ADAPTIVE KNOWLEDGE BASE CONSTRUCTION METHOD AND SYSTEM

    公开(公告)号:US20180039890A1

    公开(公告)日:2018-02-08

    申请号:US15668646

    申请日:2017-08-03

    CPC classification number: G06N5/027 G06F16/9027 G06N5/025

    Abstract: Provided are an adaptive knowledge base construction system and method. The adaptive knowledge base construction system includes a machine learning engine analyzing a correlation between pieces of data included in a first data set in a process of learning the first data set input thereto, based on machine learning, a rule generator generating a rule based on the machine learning by using an analysis result obtained by analyzing the correlation, and a semantic rule generator generating a semantic rule from the rule based on the machine learning by using a language expressing ontology, and reflecting the generated semantic rule in a knowledge base to extend the knowledge base.

    METHOD AND SYSTEM FOR SELECTING THINGS BASED ON QUALITY OF SERVICE IN WEB OF THINGS
    4.
    发明申请
    METHOD AND SYSTEM FOR SELECTING THINGS BASED ON QUALITY OF SERVICE IN WEB OF THINGS 审中-公开
    基于网络质量的选择方法和系统

    公开(公告)号:US20160277532A1

    公开(公告)日:2016-09-22

    申请号:US14936992

    申请日:2015-11-10

    Abstract: A method and system for recommending a thing based on quality of service in a web of things environment, the method including (a) obtaining web log data and metadata of at least one thing; (b) computing QoS (Quality of Service) features of the thing from the web log data and metadata; (c) in response to obtaining user's review information on the thing, computing QoS grade information on the thing from the review information; and (d) generating a rule for predicting a QoS grade for a thing for which there is no user's review information with reference to the QoS grade information on the thing and the QoS features of the thing.

    Abstract translation: 一种用于在事物环境中基于服务质量推荐事物的方法和系统,所述方法包括(a)获得网络日志数据和至少一件事情的元数据; (b)从Web日志数据和元数据计算物品的QoS(服务质量)特征; (c)响应于获取用户对该事物的审查信息,从审查信息计算事物的QoS等级信息; 以及(d)参照关于物品的QoS等级信息和物品的QoS特征,生成用于对没有用户审查信息的事物预测QoS等级的规则。

    INTERNET OF THINGS TERMINAL AND METHOD OF FILTERING CONTENT INCLUDING PRIVACY INFORMATION IN THE SAME

    公开(公告)号:US20200233969A1

    公开(公告)日:2020-07-23

    申请号:US16273483

    申请日:2019-02-12

    Abstract: A method of filtering content including privacy information in an Internet of things (IoT) terminal includes generating, by the processor, content management data prescribing a mapping relationship between pieces of content, a kind of a network, and a plurality of applications and storing the content management data in a content management data storage unit, based on a user input, the content management data prescribing a security policy associated with external transmission of the pieces of content, and when an external transmission request message corresponding to specific content of the pieces of content is received from the specific application, determining, by the processor, whether to allow external transmission of the specific content in response to the external transmission request message, based on the security policy prescribed in the content management data.

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