SYSTEM AND METHOD FOR FRAUD DETECTION THROUGH NETWORK MONITORING

    公开(公告)号:US20250113193A1

    公开(公告)日:2025-04-03

    申请号:US18477699

    申请日:2023-09-29

    Abstract: Aspects of the subject disclosure may include, for example, a device, having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: collecting data traffic of one or more network devices of a user, wherein the data traffic is associated with multiple channels of interactions; building a channel-specific user signature and a cross-channel user signature of normal usage for the user based on the data traffic collected; detecting a change in a characteristic of the data traffic, wherein the change indicates fraudulent activity based on the channel-specific user signature and the cross-channel user signature; and issuing an alert of the fraudulent activity based on the change. Other embodiments are disclosed.

    SENTIMENT ANALYSIS TUNING
    13.
    发明申请

    公开(公告)号:US20210081617A1

    公开(公告)日:2021-03-18

    申请号:US17107898

    申请日:2020-11-30

    Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for sentiment analysis tuning. In one example, the method, includes acquiring a first sentiment analysis-generated score for a first string of text, wherein the first string of text includes a first plurality of words, and wherein the first sentiment analysis-generated score is calculated using a set of first values associated with the first plurality of words, calculating a second value for at least one word of the first plurality of words, based on a non-sentiment-analysis generated score associated with the first string of text, acquiring a second string of text, wherein the second string of text includes a second plurality of words, and wherein the second plurality of words includes the at least one word, and calculating a sentiment analysis-generated score for the second string of text, using the second value for the at least one word.

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