Electronic device and control method therefor

    公开(公告)号:US11531722B2

    公开(公告)日:2022-12-20

    申请号:US17284401

    申请日:2019-07-02

    Abstract: The present disclosure provides an electronic device and a control method therefor. An electronic device of the present disclosure may comprise a memory including at least one command, and a processor which is connected to the memory so as to control the electronic device, wherein the processor executes at least one instruction, so as to classify a uniform resource locator (URL) corresponding to at least one website accessed by a user during a preconfigured period into at least one segment, classify URLs according to a plurality of categories, on the basis of the at least one segment and a learned classification model, and determine, among the plurality of categories, a category of a website preferred by the user, on the basis of the user's website access history during the preconfigured period, an access history with respect to the at least one website, and a result of the classification. The electronic device of the present disclosure may use a rule-based model or an artificial intelligence model learned according to at least one of a machine learning, a neural network, or a deep learning algorithm.

    Electronic device and control method thereof

    公开(公告)号:US11500742B2

    公开(公告)日:2022-11-15

    申请号:US16768741

    申请日:2018-12-19

    Abstract: An electronic apparatus is provided. The electronic apparatus includes a storage storing error-related information of an external electronic apparatus, and a processor configured to obtain first error-related information with respect to a target time interval and second error-related information with respect to a standard time interval including the target time interval and time intervals other than the target time interval, from the storage, obtain frequency information for each number of error occurrences with respect to the target time interval based on the first error-related information and frequency information for each number of error occurrences with respect to the standard time interval based on the second error-related information, and compare the frequency information for each number of error occurrences with respect to the target time interval with the frequency information for each number of error occurrences with respect to the standard time interval to identify an error occurrence level with respect to the target time interval.

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