18 results about "Group discovery" patented technology

A radio frequency (RF) IoT device may be configured to receive a group discovery query for a set of IoT devices from an RF source device. The group may be based on at least one of (a) an IoT device class, (b) a measurement type, (c) a data priority, (d) a type of information carried by the set of IoT devices, (e) a presence of data, (f) an amount of the data, (g) a distance from the RF source device, or (h) a set of identifiers for the one or more IoT devices in the group. The RF IoT device may be configured to transmit a response to the group discovery query based on the IoT device belonging to the set of IoT devices.

The invention discloses a social group discovery system based on fused semantic information. The system comprises a presentation layer, a presentation layer, a service layer and a data layer. The presentation layer supports checking of a group division result; the display layer displays a user structure network, group dynamic division and group characteristic indexes through a visual tool; the service layer is composed of a semantic tag generation module, a user structure analysis module, a social group division module and a social group analysis module, semantic and structural features are fused through a graph attention network, and accurate group division is realized in combination with an adaptive embedded graph aggregation algorithm; and the data layer stores the original data set of the social platform and the processed data. The system inputs user texts into a large language model to generate semantic tags, node embedding is generated by calculating node association weights, group division is completed by combining an adaptive embedding graph aggregation algorithm, and finally group characteristics are quantitatively analyzed from the aspects of cohesion, conductivity and the like. The system is suitable for scenes such as vertical domain community mining.

A method, system and apparatus for group management for vehicle-to-anything (V2X) and Proximity Based Services (ProSe) groupcast. According to one aspect, a method in a wireless device (WD) includes discovering wireless devices (WDs) that are members of a group, and sending to the WDs that are members of the group a group discovery complete message. According to another aspect, a method in a WD includes listening for a group discovery signal indicating a group to which the WD belongs or seeks to join, and sending a group discovery response indicating that the WD seeks to join or remain in the indicated group.

The embodiments of this specification disclose a group query method, apparatus, and device, belonging to the field of graph data technology. The method includes: obtaining node-related data for offline calculation, wherein the offline calculation includes: a priori step, a setting step, and a discovery step; in the priori step, obtaining group prior knowledge of a portion of nodes in a graph topology data set; in the setting step, setting group labels for each portion of nodes as supervision data based on the group prior knowledge, and initializing the group labels of each remaining node; in the discovery step, performing group discovery in the graph topology data set based on the supervision of the supervision data and the initialized group labels; synchronizing the results of the group discovery to an online storage database; and upon receiving a query data set containing multiple nodes submitted by a user, querying the online storage database for the groups to which at least some of the multiple nodes belong, and responding to the user based on the query results.

Security and privacy mechanisms are provided to protect the L2 identifiers used in groupcast communications over the sidelink (e.g., PC5 interface) without requiring a UE to periodically refresh the L2 identifiers, which may cause extra signaling overhead, increased latency and greater risk of synchronization issues. To prevent tracking of a UE, a group identifier (ID) is used as a source layer 2 (L2) ID in groupcast messages. Additionally, a message authentication code (MAC) is introduced into the group discovery procedure to authenticate the UE sending a group discovery request.

The present invention provides a ranging or positioning method and apparatus, a communication device, a communication system, and a storage medium. The method comprises: a first network element may send group discovery information to a first terminal, wherein the group discovery information is used for indicating that a second terminal belongs to a first terminal group, and the second terminal is used for performing ranging or positioning on the first terminal. According to the method of the present invention, a first network element may timely indicate group discovery information to a first terminal, thereby implementing ranging or positioning on the first terminal on the basis of a second terminal in a first terminal group.

The embodiment of the invention relates to the technical field of computers, and discloses an account management method, electronic equipment, a storage medium and a computer program product. The account management method comprises the following steps: clustering content data of a plurality of accounts, and constructing an association relationship between the accounts and the content data; determining at least one target group in the association relationship based on a group discovery algorithm; performing semantic analysis on the content data to identify a group category of the target group; and managing the account of the target group according to a processing strategy corresponding to the group category. The beneficial effects of the invention are that the method can achieve the precise recognition of the group behavior of the account, and achieves the targeted management of the account.

The present invention provides a group discovery method based on searching conditional dense subgraphs in a large symbolic graph, and relates to the field of information processing technology. The method includes: generating an initial symbolic graph based on social data to be searched; sorting the vertices in the initial symbolic graph to obtain the sorting results, and sequentially generating the total branches corresponding to each vertex according to the sorting results; branching the total branch at least once to obtain a target sub-branch, and the target sub-branch meets the preset conditions. At each branch, the pivot point is determined based on the number of second symbolic neighbors of the vertex in the union of the candidate set and the required set of the parent branch, and the sub-branch is generated based on the pivot point; based on the target sub-branch with the largest number of vertices, the target group in the social data to be searched is determined. The present invention can find groups with close relationships and consistent relationship types from a large amount of social data, thereby improving the accuracy of content recommendation based on the group.

The embodiment of the invention provides a group discovery method and device, and electronic equipment, and the method comprises the steps: filtering out the track cluster of registered personnel not participating in analysis from all obtained personnel track clusters, and obtaining a first personnel track cluster; according to the first person track cluster, respectively calculating intimacy values between each first person and other persons; filtering out registered analysis participants contained in the first personnel to obtain unregistered first personnel; for each unregistered first person, screening out intimate peers according to the intimacy values between the unregistered first person and other persons; and according to a preset rule, determining groups to which the unregistered first personnel and the intimate peers belong, and obtaining personnel included in each group. The group discovery scheme provided by the invention can improve the accuracy of the group discovery result, and has good generalization.

The invention relates to the technical field of biological analysis, discloses a group discovery method and device for a dynamic metabolic network, introduces the concept of time smoothness to solve the problem of instability of a group structure in the dynamic network, and improves the stability and accuracy of the group structure. Based on the thought of evolution clustering and semi-nonnegative matrix factorization, the model fuses node similarity into network analysis, the topological structure and the similarity relation between the nodes in the metabolic network are comprehensively considered, and the problem that group division is insufficient in other methods is effectively solved. Meanwhile, by processing the microstructure of the metabolic network, the system can effectively solve the problem of data sparseness, and enables the relation between the nodes in the group to be tighter. Besides, the system effectively improves the distinction degree among the groups and reduces the influence of noise through a method based on semi-non-negative matrix factorization (Semi-NMF), thereby improving the accuracy and reliability of group discovery.

This invention relates to the field of e-commerce technology, and more specifically, to a method for expanding and selecting e-commerce audiences based on similarity group discovery. The method includes: collecting samples to be cleaned from multiple data sources; selecting corresponding modal encoders and modal enhancement strategies based on data source identifiers; achieving cross-modal feature space alignment by constructing a set of positive sample pairs and a set of negative sample pairs and performing comparative learning training; obtaining a final group set through multi-table joint candidate set construction and fine clustering; solving for the hyperspherical prototype center using Riemann gradient descent for each final group; labeling normal or abnormal samples based on comparison results; and outputting the cleaned dataset and the abnormal sample set. This invention solves the problem of incomparability of feature spaces in multi-source heterogeneous data, improves the efficiency of large-scale data processing, maintains the geometric consistency of the manifold space, and achieves adaptive determination of the anomaly detection threshold.

The embodiment of the present application provides a group discovery method and device, and an electronic device, wherein the method includes: filtering out the trajectory clusters of registered non-analyzed persons from the acquired trajectory clusters of each person, to obtain a first person trajectory cluster; calculating the intimacy values ​​between each first person and other persons based on the first person trajectory cluster; filtering out the registered participants in the analysis included in the first person, to obtain unregistered first persons; for each of the unregistered first persons, screening out close companions based on the intimacy values ​​between the unregistered first person and other persons; determining the groups to which each of the unregistered first persons and close companions belongs according to preset rules, to obtain the persons included in each group. The group discovery solution provided by the present application can improve the accuracy of group discovery results and has good generalization.

The invention provides a group discovery method based on a search condition dense subgraph in a large symbol graph, and relates to the technical field of information processing, and the method comprises the steps: generating an initial symbol graph based on to-be-searched social data; sequencing the vertexes in the initial symbol diagram to obtain a sequencing result, and sequentially generating total branches corresponding to the vertexes according to the sequencing result; performing at least one branching on the total branch to obtain a target sub-branch, the target sub-branch satisfying a preset condition, during each branching, determining a pivot point based on the number of second symbol neighbors of a vertex in a union of a candidate set and a necessary set of the parent branch, and generating the sub-branch based on the pivot point; and determining a target group in the to-be-searched social data based on the target sub-branch with the maximum vertex number. According to the method, the groups which have close relations and consistent relation types can be searched from a large amount of social data, so that the accuracy of content recommendation based on the groups is improved.

The application belongs to the field of guided topic network analysis, and particularly relates to a social network group discovery method based on user preferences, comprising: obtaining relevant information from a social network platform; calculating the interaction degree and reputation degree of users; defining a random walk strategy of IBT2vec algorithm, and representing the user topic network as a feature vector matrix; using RoBERTa to obtain the long-term and short-term preferences of users, fusing the same with the initial feature vector to form an enhanced user node representation; compensating for the network space features through meta-transfer learning to alleviate the data sparsity problem; classifying the user features through a spectral clustering method, and obtaining key influential user groups with similar interests and behaviors after full connection layer and normalization processing. The application not only considers the similarity between users, but also comprehensively considers the influence of users, so that the group discovery is more accurate and practical, and reliable support is provided for applications such as public opinion monitoring, information dissemination and marketing promotion.

A method, computer program product, and computer system are provided for user access group discovery. The method includes: generating a matrix that depicts the respective resources of a set of resources accessed by each of a plurality of users; obtaining, for each user, a similarity measurement using the matrix, wherein the similarity measurement is based on a comparison of the resources accessed by the user to the resources accessed by the other users; generating, for each user, a feature vector for clustering the users into user access groups, wherein the feature vector represents the resources accessed by the user; applying the feature vectors and the similarity measurements to a centroid-based clustering algorithm to obtain the user access groups; and outputting the user access groups for application in a security environment.

A method, computer program product, and computer system are provided for user access group discovery. The method includes: generating a matrix that depicts the respective resources of a set of resources accessed by each of a plurality of users; obtaining, for each user, a similarity measurement using the matrix, wherein the similarity measurement is based on a comparison of the resources accessed by the user to the resources accessed by the other users; generating, for each user, a feature vector for clustering the users into user access groups, wherein the feature vector represents the resources accessed by the user; applying the feature vectors and the similarity measurements to a centroid-based clustering algorithm to obtain the user access groups; and outputting the user access groups for application in a security environment.

Techniques are provided for ad-hoc authenticated group discovery and data sharing in a mesh network. A group of devices is created without leaving a security gap due to the open communication needed to establish the discovery of the devices forming the group. The group can be authenticated autonomously following network discovery of the devices. Instead of requiring global pre-assigned keys for authentication, the devices in the group are authenticated with signatures and certificate passing thereby providing strong security. The efficiency of data sharing between the devices of the network, such as a mesh network, can also be increased. One or more devices may act as a bridge device between devices of a same group that are not in direct wireless communication with each other to reduce re-broadcasts within the mesh network.

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.