8 results about "Social account" patented technology

The present disclosure relates to social account recovery. A method is provided that includes receiving, by a server from a user device, a first value computed as a hash of a first key and a user identifier, determining, by the server, that the first value matches a previously computed value used to request account recovery access to an account of a user corresponding to the user identifier, and enabling an account recovery mode in response to a determination, by the server, that the first value matches the previously computed value used to request account recovery access to the account of the user.

Systems and methods are provided for performing operations including: receiving, via a messaging application of a user device, a request to recover access to an account of a user of the messaging application; accessing a first object corresponding to a first key; receiving, from a first friend of the user on the messaging application, a second object corresponding to a first portion of a second key; receiving, from a second friend of the user on the messaging application, a third object corresponding to a second portion of the second key; deriving the second key based on the second and third objects; and recovering access to the account of the user based on the first key and the second key.

The present application relates to the technical field of data anomaly detection, and particularly relates to a social account operation data anomaly automatic diagnosis method and system, which firstly performs data dimension reduction in combination with fluctuation of data sampling values of each operation data dimension under multiple sub-dimensions to determine data characteristic values more representative in representing data time sequence change characteristics; then determines prediction residual according to prediction error of the data characteristic values according to characteristics of regularity patterns represented by trend, periodicity and internal dependency relationship mixed in operation data of the social account; and further comprehensively represents data regularity of the social account in the current time window in combination with characteristic data importance represented by deviation of data characteristic values of different social accounts on the basis of the prediction residual, so that the accuracy of operation data anomaly diagnosis according to the data regularity is higher.

The application relates to an information processing method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a community message published by a target community, the target community being a community of a social platform matched with a preset first type keyword and pulled and joined by the social platform after a preset social account is used to log in to the corresponding social platform; determining a target community message matched with a preset second type keyword in the community message, and extracting key information in the target community message; determining business data associated with the key information, extracting associated business information in the associated business data; and determining processing information based on the key information and the associated business information. The method can timely discover the risk of online resource leakage, timely discover security risks, and improve security.

The invention provides a cross-platform multi-social-account parallel scheduling method and device, and the method comprises the steps: responding to a received operation instruction, determining at least one target account in the operation instruction and at least one operation task associated with each target account, analyzing at least one operation sub-task corresponding to each operation task, and determining at least one operation sub-task corresponding to each operation task; the data relation between the sub-tasks is operated; and for each target account, executing each operation sub-task according to the sequence of the data relationship under the target account, pushing an execution result to an independent idle container, and issuing the execution result in the independent idle container through the target account. Therefore, through independent container management, simultaneous parallel operation of all accounts of all platforms can be realized, so that the limitation that social platforms which can only operate the same or the same system at the same time and the limitation of the number of accounts can be eliminated, and the human input of operation can be saved.

The invention relates to the technical field of data anomaly detection, in particular to an automatic diagnosis method and system for operation data anomaly of a social account, and the method comprises the steps: firstly carrying out the data dimension reduction according to the fluctuation condition of a data sampling value of each operation data dimension under a plurality of sub-dimensions; determining a data feature value representing that the data time sequence change feature is more representative; then, according to the characteristic that the operation data of the social account is mixed with a regular mode represented by trend, periodicity and internal dependency relationship, determining a prediction residual error according to the prediction error condition of the data characteristic value; furthermore, on the basis of the prediction residual error, the feature data importance represented by the deviation condition of the data feature values of different social accounts is combined, the data regularity of the social accounts in the current time window is comprehensively represented, and the accuracy of operation data anomaly diagnosis according to the data regularity is higher.

The application discloses a score suggestion generation method and device based on a social account and related media, which comprises the following steps: obtaining a social account and collecting multi-source data to obtain a multi-source original data set, and then performing data preprocessing to obtain a standardized data table; performing multi-dimensional feature extraction based on the standardized data table to obtain a feature index set; respectively performing subtask mapping and model reasoning on the feature index set to obtain a subtask evaluation result set; performing rule matching on the subtask evaluation result set, generating a required text, and integrating to obtain a strategy item set; and performing aggregation arrangement on the strategy item set to encapsulate an overview suggestion object. The application performs preprocessing and feature extraction on multi-source data based on a social account, generates a strategy through mapping reasoning and rule matching, and finally aggregates and arranges the strategy into an overview suggestion object. In this way, the advertisement platform can uniformly and standardize the cross-source account data, improve the evaluation efficiency, and realize the evaluation scaling.

The invention relates to a social account dynamic risk assessment method and system. The method comprises the steps of obtaining social behavior data of a target social account in a social media platform; performing multi-dimensional feature extraction processing on the social behavior data to obtain multi-dimensional feature parameters and initial multi-dimensional feature weights; calculating and updating a multi-dimensional feature weight according to the multi-dimensional feature parameters, the initial multi-dimensional feature weight and an artificial rechecking result; calculating a comprehensive risk value of the target social account according to the multi-dimensional feature parameters and the updated multi-dimensional feature weights; and processing the target social account according to the comprehensive risk value. According to the invention, the accuracy of social account risk assessment can be improved, and account disposal can be carried out in time.