16 results about "Social account" patented technology

The invention discloses a scoring suggestion generation method and device based on a social account and a related medium, and the method comprises the steps: obtaining the social account, carrying out the multi-source data collection, obtaining a multi-source original data set, carrying out the data preprocessing, and obtaining a standardized data table; performing multi-dimensional feature extraction based on the standardized data table to obtain a feature index set; performing sub-task mapping and model reasoning on the feature index set to obtain a sub-task evaluation result set; performing rule matching on the sub-task evaluation result set, generating a required text, and integrating to obtain a strategy entry set; and aggregating and arranging the strategy entry set, and packaging to obtain a suggested overview object. According to the method, preprocessing and feature extraction are carried out based on the social account multi-source data, the strategy is generated through mapping reasoning and rule matching, and finally the suggested overview object is aggregated and arranged, so that an advertisement platform can carry out unified standardization processing on the cross-source account data, the evaluation efficiency is improved, and large-scale evaluation is realized.

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 application relates to an information recommendation method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining an account interaction feature corresponding to a social network to which a target account belongs; the account interaction feature is obtained according to interaction behaviors between each social account in the social network; performing feature propagation mapping on an account feature corresponding to the target account through the account interaction feature, obtaining a propagation account feature corresponding to the target account according to a result of the feature propagation mapping; obtaining an information interaction feature of each to-be-recommended information; the information interaction feature is generated based on an account feature of a social account that has generated an interaction operation on the corresponding to-be-recommended information in the social network; matching the propagation account feature and each information interaction feature, and recommending a target information determined from each to-be-recommended information to a terminal corresponding to the target account according to a matching result. The method can improve the accuracy of information recommendation.

This application provides a social interaction method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product. The method includes displaying a status presentation area of a target account; presenting a first virtual image corresponding to a target status and a social interaction control in the status presentation area in response to a social status of the target account being the target status; transmitting social interaction invitation information to a terminal corresponding to the target social account in response to a social invitation operation on a target social account triggered by the social interaction control; and replacing the first virtual image with a second virtual image corresponding to the target status when the target social account accepts the social interaction invitation operation, the second virtual image indicating that the social relationship is established between the target account and the target social account.

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 invention relates to a multi-social-login system based on an Oauth2 protocol. The multi-social-login system comprises a resource server, a system authorization server and at least two social authorization servers, wherein the system authorization server is used for login authorization of a system account; the social authorization server is used for login authorization of a third-party social account; the resource server calls a system authorization server for authentication so as to judge whether the current user has logged in the system and obtain access authorization of the system; if the authentication of the system authorization server is successful, the current user continues to access; and if the authentication of the system authorization server fails, performing authentication login in response to any social login request. According to the invention, multi-platform social login can be realized.

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 present invention discloses a social data collection method and device. The method obtains relational data of all first social accounts in a main community to be observed and a set of characteristic word groups corresponding to the main community. Based on the relational data, the method obtains the second social account corresponding to each first social account to generate a corresponding sub-community. The method then obtains information about the second social account in the sub-community to generate a characteristic word group. The method determines the relationship between the second social account and the main community based on the relationship between the characteristic word group and the set of characteristic word groups. In this way, the method can track the second social account related to a group event in the main community in the current time period, add the second social account to the main community for monitoring, and thus effectively associate the participants of the group event and collect the corresponding event information. The addition of the second social account to the main community also realizes the dynamic expansion of the main community, thereby realizing the dynamic monitoring of the development of the group event.

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.

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 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.

The invention relates to the technical field of network behavior management and topology construction, in particular to a group discovery method, device and system in a social forwarding network. According to the group discovery method in the social forwarding network, starting from a topological structure, namely a directed propagation network, of social behaviors, primary and advanced dependency relationship networks are constructed to identify candidate groups, and then the distance between the candidate groups is analyzed to obtain an account relationship network of a tree structure. According to the method, the social account weight is fully considered through network evolution, and the structural layering of the relation network is realized through network simplification, so that the linear time complexity of the social relation network is improved, and the reliability of group analysis and the integrity of social behavior analysis are ensured.

The invention relates to a style text generation model training method and a style text generation method. The method is suitable for information processing technology. According to the technical scheme, the style text generation model training method is characterized by comprising the steps that S1, social account basic information and historical stickers of a target person are obtained, and titles, abstracts and core content are extracted from the historical stickers in multiple extraction modes; s2, constructing a training sample set based on the title, the abstract or the core content in combination with the corresponding historical post and the basic information of the social account; and S3, based on the training sample set, training the pre-trained large language model to obtain a trained style text generation model.