12 results about "Pagerank algorithm" patented technology

The application discloses a power grid power transmission section identification method based on an improved PageRank algorithm and network conversion, first, an improved PageRank algorithm is used to calculate a node criticality index, and a network constraint coefficient is calculated according to a network topological structure and is used to correct a restart vector; second, a key power transmission section search topological graph is constructed through network conversion and node criticality index calculation, and identification of the key power transmission section is converted into search of a shortest path; finally, according to energy transaction between a generator node and a load node, a search range of the key power transmission section is set, a related cut set with the highest criticality is found, and through checking and correction, an identification result of the key power transmission section is obtained. The application can well improve the deficiency of the original PageRank algorithm when applied to the power grid, can accurately identify the power transmission section of the power grid, provides a key monitoring guide for power grid monitoring and dispatch personnel, and better guarantees the safe and stable operation of the power grid.

This invention discloses a PageRank-based agent discovery method and system. The method involves initializing the agent discovery system's agent list, comprehensive scoring weight parameters, and system configuration; associating basic information with agent skill information to form a skill candidate list; calling an API to generate semantic vectors for candidate skills and task descriptions in the skill candidate list through semantic pre-screening, calculating cosine similarity as the basic matching degree, adding a matching bonus score to the basic matching degree to obtain a semantic enhancement score, and sorting the semantic enhancement scores; calculating and weighting the PageRank score, call frequency score, call success rate score, and recent activity score; sorting the scores and returning the top M results to the user. The method models the agent's historical call records as a weighted directed graph and uses the PageRank algorithm to quantify the global importance of nodes, transforming the retrieval process into a graph traversal guided by a "importance-relevance" dual-factor approach, significantly reducing the inclusion rate of irrelevant results.

This invention discloses a GCN-based method for detecting stegchmakers in social networks, addressing the challenge of stegchmaker detection in these networks. First, a social network graph is constructed, with active users and comments designated as nodes, and user replies as directed edges with attributes (interaction frequency, content similarity, and reply time) to analyze social interactions and potential steganographic behavior. A personalized PageRank algorithm is employed, using known stegchmaker nodes as seeds to construct vectors. Weights are adjusted based on edge attributes, and the PageRank value of each node is iteratively calculated to determine the association between the node and the stegchmaker. Simultaneously, GCN is utilized to capture syntactic and semantic connections between words, and features are processed using ResNet to fuse local and global information, optimizing the understanding and processing capabilities for complex graph structures. Experiments determine the weights of text feature scores and PageRank values, comparing the performance of different methods on Reddit and Twitter datasets. This verifies that the proposed method effectively captures steganographic behavior and improves detection accuracy under different loads and encoding strategies, providing a new approach and technical support for steganalysis in social networks.

A method and system for generating personalized content for elderly care and wellness based on knowledge graphs and multimodal AIGC includes the following steps: 1) acquiring multi-source structured data in the field of elderly care and wellness, and multi-dimensional profile data of target users. The multi-source structured data sources include structured databases, medical encyclopedias, and clinical guidelines, while the multi-dimensional profile data includes static attribute data, dynamic behavioral interaction data, and user historical preference data; 2) constructing an elderly care and wellness knowledge graph, defining the core entities, attributes, and relationships of the knowledge graph; 3) using a personalized PageRank algorithm, based on the knowledge graph, retrieving a list of relevant entities ranked by global network importance from the multi-dimensional profile data; 4) using template-based interpolation and dynamic routing algorithms to combine the list of relevant entities ranked by global network importance with the generation scenario, automatically assembling it into a structured Prompt instruction; 5) calling a multimodal AIGC composed of a large language model and a diffusion model to generate personalized content such as articles, images, and audio / video based on the Prompt instruction; and 6) presenting the finally generated content to the target user. This invention can deeply understand elderly users and tailor content generation instructions for them.

This invention discloses a method and system for regional and national hotspot mining and briefing generation based on complex networks and large language models, belonging to the field of natural language processing and public opinion analysis technology. The method includes: collecting, cleaning, deduplicating, and sorting multilingual public opinion data; constructing a news dissemination network based on temporal semantic similarity and using connected component algorithms to discover hotspot communities; performing quality assessment and topic consistency optimization on the communities, and selecting representative texts using an improved PageRank algorithm; and automatically generating structured briefings including event summaries, knowledge graphs, news rewriting and commentary, and hotspot extensions by combining preset prompt templates with a generative large language model. This invention can effectively capture the dynamic evolution of multilingual public opinion, improve the accuracy and completeness of hotspot event mining, achieve full automation from data collection to report generation, and significantly improve the efficiency and depth of regional and national public opinion analysis.

This invention relates to the field of hepatitis B pharmacology, and discloses a method for identifying targets of traditional Chinese medicine (TCM) for chronic hepatitis B based on graph neural networks. First, the active ingredients and potential targets of at least two TCM formulas are extracted, and "TCM-component-target" networks are constructed respectively. From a TCM systems pharmacology database network, the degree centrality, betweenness centrality, and eigenvector centrality of node i in the data network are used as identification indicators for key nodes. Topological analysis is used to screen key nodes in the network, and then the importance of node i is comprehensively ranked using the PageRank algorithm. The core components and targets that rank highly in all TCM formulas are calculated. By constructing a modular network, the common components and target groups in the TCM formulas are calculated. Simultaneously, GO function and KEGG pathway enrichment analyses are performed to calculate the biological functions and signaling pathways associated with key targets. This invention utilizes molecular docking technology to verify the interaction between core targets and small drug molecules.

The application relates to a hospital management scene simulation and evaluation method and system based on a generative adversarial network, which comprises the following steps: collecting hospital full-dimension management data, and generating a management data matrix through time-space alignment and standardization. Unsupervised learning is performed through a restricted Boltzmann machine to output an index probability distribution model and a connection weight matrix. A hospital management graph is constructed based on this, and an improved PageRank algorithm is used to calculate a node management importance score. In combination with a management target, graph embedding and adaptive clustering are performed to obtain a node embedding vector and a classification label set. The connection weight matrix, the importance score and the classification label are comprehensively used to calculate a comprehensive management evaluation score. Finally, the probability distribution model, the evaluation score, the classification label and an external intervention strategy are input into a generative adversarial network, and after adversarial training, a dynamic management scene prediction report and an optimization strategy scheme are output, so that the scientificity and the fine-grained level of hospital management decision-making are improved.

The application discloses a kind of power system broadband oscillation damping coefficient intelligent calculation method, comprising the following steps: S1, sample generation;S2, based on PageRank algorithm, the importance of measuring point is sorted;S3, measuring point damping coefficient calculation;S4, system damping coefficient enhancement.The application has high precision: it can effectively improve the precision of system oscillation risk assessment to 98.5%;Measurement requirement is low: system oscillation risk assessment can be realized under the measurement signal of about 40% or so line of system;Fast calculation speed: compared with traditional CPU-based oscillation risk assessment, GPU is called by neural network embedded calculation, and the calculation speed is about 16 times higher.

The application provides a satellite network international cooperation relationship mining method and system, the method is based on a satellite network data database, a satellite network correlation relationship network is constructed, and a Louvain algorithm and a PageRank algorithm are used to mine satellite network country cooperation relationships; the country cooperation relationships include community distribution of the cooperation relationship network, importance of the countries in cooperation, and cooperation business types of the countries in satellite network engineering. The application applies graph theory to satellite network international cooperation relationship mining, can automatically analyze hidden cooperation relationships between countries from the ITU satellite network data database through the graph algorithm without prior knowledge, saves manpower, and has good effects on mining implicit cooperation relationships.

The application relates to the technical field of context management, in particular to a method for optimizing a context window of a large model based on cognition. In the application, a PageRank algorithm is used to perform iterative updating on a directional correlation weight and output an entry importance distribution, the ratio of importance to length is entered into sorting and reserved items are selected under capacity constraints, multiple conclusion dependent evidence is entered into a forced reserved path, contradictory evidence is entered into an exclusive selection and replacement numbering registration path, a finite state machine is used to filter windowable entries according to a context stage identifier, and a life cycle marker and version number are linked to exclude expired conflict content, conclusion numbers are aggregated to form aggregated units and an index placeholder is written for excessive units, non-referenced units are executed to reserve index mapping, the probability of forgetting and repeatedly asking in cross-round interaction is reduced, window occupancy fluctuation converges, invalid reasoning overhead and calculation cost are reduced, and the proportion of task target related information is increased, thereby improving output consistency.