42 results about "Event structure" patented technology

The invention provides an intelligent factory management method and system based on the industrial internet, and the method comprises the steps: obtaining original data of a multi-source heterogeneous device, and generating a semantic event structure through preprocessing; the industrial event sequence is mapped into nodes, candidate edges are generated in combination with the physical topology connection relation of the equipment, and a target causal map is constructed; according to the target causal atlas, calculating a node risk score of each event node, and performing balance adjustment on the score by using a graph-level centrality value to generate a normalized node risk score of each event node; mapping the node risk scores to devices, and calculating a risk average value of each device; and converting a scoring matrix of the current task to all candidate devices into a scheduling strategy value, executing a scheduling strategy and collecting task execution feedback, and dynamically adjusting a target causal atlas and a node risk score according to the difference between an actual result and a predicted value to realize dual optimization of the target causal atlas and the scheduling strategy.

Techniques for a service provider network to communicatively couple services and / or applications in a serverless computing environment. A pipe component can configure a pipe to integrate two services by transmitting data between services and / or applications using the pipe. The pipe may also be configured to transform how a service processes an event, control timing of event transmissions using the pipe, define an event structure for an event, and / or batch events. Pipes enable an application or service to exchange data with a variety of services provided by the service provider network while controlling what type of data is generated, stored, or transmitted.

The invention provides a block chain-based clinical test data traceability and sharing platform. The block chain-based clinical test data traceability and sharing platform comprises the following modules: a life cycle state definition module, an on-chain event generation module, an identity verification module, a state transition logic unit and an event chain construction module. According to the invention, through cooperation of a life cycle state definition module, an on-chain event generation module, a state transition logic unit and an event chain construction module, key behaviors generated by a subject in the stages of screening, informed agreement, group entering, visit, adverse event processing, follow-up visit and the like are solidified into a chain event structure according to a time sequence; each event node comprises a behavior abstract, a preorder node hash and a timestamp, continuous association and accurate positioning of cross-stage operation are achieved, a clinical test is converted into a state transition chain capable of tracking the whole process from a fragment type data uplink, and the problem that a continuous behavior chain cannot be constructed in the prior art is solved.

The invention provides a technical and economic risk event extraction method and system based on monitoring entities, and relates to the technical field of entity extraction, and the method comprises the steps: carrying out the entity recognition of a multi-source science and technology text, carrying out the entity comparison and screening of technical and economic monitoring entities, and outputting a candidate monitoring entity list; performing semantic fragment extraction by taking the candidate monitoring entity list as an anchor point, and performing event type judgment based on a trigger word matching rule; performing dependency syntactic analysis and semantic role labeling on the trigger word set, constructing a standardized event structure, extracting a semantic relationship, and outputting a risk event candidate structure set; identifying chapter-level master events, and aggregating paragraph-level associated events to form a master-slave event structure; and assembling the event chain according to the master-slave event structure, and performing standardized output. By means of the method and device, the technical problem that in the prior art, the reliability of extraction of economic risk events is poor can be solved, and the technical effect of improving the reliability of extraction is achieved.

The present invention provides a script event extraction method, device, electronic device and storage medium. First, the script text to be extracted is obtained; then, dependency analysis is performed on the script text to be extracted to determine the dependency graph corresponding to the script text to be extracted; finally, the dependency graph is input into an event extraction model to obtain the target category of the target event structure element of the script text to be extracted under the target event type. The method introduces dependency analysis to determine the dependency graph in view of the characteristics that the script event structure elements have hierarchical correlation, and adopts a combination of dependency analysis, attention mechanism and graph attention mechanism to semantically supplement the words in the dependency graph, realize script event extraction, determine the event type in the script text and the category of each event structure element under the specific event type, can have good universality, enhance the semantic expression ability of the feature vector, and improve the accuracy of script event extraction.

The invention discloses a syntactic selection simulation method, system and equipment based on event structure and syntactic frequency interaction. The method belongs to the technical field of dynamic simulation of Chinese syntax generation, and comprises the following steps of: 1, analyzing a question element role relationship of an input event, and generating an event structure vector; 2, calling a syntactic frequency database, and obtaining the use frequency weight of the candidate sentence pattern; 3, calculating the verb semantic distance between the target event and the historical event; 4, dynamically generating a syntactic selection probability through interaction; 5, when the events are the same and verbs are multiplexed, the syntax selection probability is adjusted. Through multi-dimensional interactive modeling of the event structure, the syntactic frequency and the semantic information, more accurate and natural syntactic selection simulation conforming to human language behavior rules is realized, and the intelligent level and simulation authenticity of a language generation system are remarkably improved.

The invention discloses a document-level event argument extraction method and system based on a semantic fusion graph, and the method comprises the steps: building a semantic mention graph by taking entity mentions in a document as nodes of the graph and semantic relationships as edges, fusing a graph structure into a large language model for embedding representation through a multi-layer encoder, and dynamically updating node and edge information through an attention mechanism. The embedded representation of the enhanced context semantics is obtained; constructing an event graph based on all event structures in the document, modeling a multi-event association relationship, and fusing the multi-event association relationship into a large language model decoder to strengthen the understanding of the model on the association between events; the method comprises the following steps: constructing cue sentences according to event types, synchronously inputting multi-event cue sentences in a training stage, designing a weighted loss function, guiding a model to learn multi-event information interaction, inputting the multi-event cue sentences in a reasoning stage, and only taking a target event argument result as an evaluation standard. According to the method, document noise can be suppressed, the problems of scattered distribution and long-distance dependence of events and arguments are solved, and the accuracy and robustness of argument extraction are improved.

This invention discloses a multimodal event joint extraction method based on a link matrix. It determines the event structure system of the application domain and constructs a cross-modal event extraction dataset. A link matrix between image patches and text sequences is constructed. A multimodal event extraction model is built based on ViLT, where the multimodal Transformer encoder takes image patch pixel features, word instance features, and image patch-text word instance pair features as input to obtain a multimodal feature input decoder, acquiring image-text event type consistency features, event type features, and image-text event element features. Using maximum likelihood estimation, the image-text event type matching result with the highest probability, the event type, and the image-text event element are taken as an index, and the text event information is obtained by index mapping. This invention solves the problems of low recognition accuracy in weakly supervised and unsupervised methods and inaccurate matching of pipeline-style multimodal event element information, providing a new event extraction strategy for the field of multimodal information extraction.

The invention relates to the technical field of network security monitoring, in particular to a block chain-based network data security monitoring system, which comprises a pre-chain event integration module, a field writing constraint module, an event evolution verification module, a structure association verification module and an evidence storage control module. According to the method, semantic-level integration and session-level continuous identification are carried out on the communication flow, so that the security event forms a record by taking complete communication semantics as a basic unit, the event field state has consistency and interpretability, the evolution sequence is corrected in the event time direction and the connection state level, the communication process is prevented from being mistakenly split, and the communication efficiency is improved. Through cooperative verification of communication object behaviors and response states, a single event structure is ensured to be complete and conform to security monitoring semantics, and a condition matching and sequence adjusting mechanism is introduced in a writing process, so that event records have verifiable evolution trajectories and non-repudiation evidence storage results, and the reliability of the event records is improved. And the credibility and audit value of network security monitoring are improved.

The invention relates to a traffic network security event extraction method based on machine reading understanding, which performs joint training and optimization on a trigger word prediction module and an argument extraction module by sharing a coding layer of a pre-training language model, so that two tasks promote each other in a shared semantic space. Accurate context constraints are provided for argument role judgment through trigger word recognition, disambiguation of trigger word types is facilitated through argument information, and the deep interactive optimization mechanism enables the model to learn collaborative representation sensitive to the whole event structure. Therefore, the overall accuracy of event extraction and the generalization ability of the model are remarkably improved, and the inherent error propagation problem in a traditional assembly line method is solved.

The invention relates to the technical field of data processing, in particular to a negative information real-time capturing method and system based on a web crawler, and provides the following scheme that cross-platform and multi-mode observation data are obtained through a distributed crawler, and a narrative graph is constructed in a topological manifold space. A topological evolution mechanism based on curvature contraction is adopted for a narrative graph, and a topological gravitation well structure reflecting event consistency is generated through sequential aggregation and cross-layer folding operation of a local neighborhood. And measuring the generation and disappearance processes of the topological gravitational well structure, and judging whether multi-source observation data is derived from the same event or not according to a persistence parameter, so that real-time identification and early warning of negative information are realized. The method is suitable for a social media environment which changes rapidly and is dense in noise, stable tracking of an event structure can be kept under the conditions that semantic expression is unstable and information is carried or rewritten for multiple times, and the accuracy and timeliness of negative information detection are improved.

The application relates to the field of artificial intelligence and knowledge graph, and discloses a time sequence event question and answer method based on structured subgraph retrieval, which comprises the following steps: performing text retrieval on event facts to obtain background information according to a question and answer request; analyzing the request in combination with the background information, extracting corresponding event structure constraints and time constraints; strictly screening event facts from a time sequence knowledge graph according to the constraints, and constructing an event subgraph with time attributes; performing adaptive retrieval generation on the subgraph, uniformly compressing along the time dimension or supplementing knowledge by using text retrieval, and obtaining a final subgraph after adaptive processing; and generating a time sequence question and answer result based on the subgraph. The application retains the structure and time constraints of the time sequence graph, overcomes the input length limitation of the model, and can significantly improve the question and answer accuracy and stability without fine-tuning the model.

The invention discloses a high-concurrency processor architecture based on an instruction level event structure and a scheduling method of the high-concurrency processor architecture, which are characterized in that on the basis of an RISC-V instruction, stagnation, successful termination, sequential execution, conditional branching and merging operations of a program are defined through a process algebra PA-ISA oriented to an instruction set architecture; on the basis of PA-ISA, a dependency relationship among instructions in program execution is described through an instruction level event structure IES. According to the method, an instruction-level event structure model is adopted to describe a dependency relationship among instructions in a program, so that the concurrency of the instructions is improved, and good expansibility is achieved; a high-concurrency processor architecture based on IES is combined with an asynchronous circuit, event triggering is used as a basic execution propulsion mode, and the frequency or energy efficiency is improved; by simplifying a bypass control mechanism in out-of-order execution, the system reliability is improved; through combination of an instruction-level event structure and a double-path fetch mechanism, instruction waste and performance loss are reduced, and the fault-tolerant capability under a large-scale fetch strategy is optimized.

The present invention provides a method and device for reverse generation of text data based on event patterns, the method comprising: extracting event trigger words and event argument roles corresponding to the event type from event trigger words and argument candidate vocabulary based on a preset event type; generating corresponding temporal event quintuples based on the preset event type, the extracted corresponding event trigger words and event argument roles, and the corresponding event argument roles, and forming structured text data; inputting the structured text data into a large language model so that the large language model outputs event text data corresponding to the preset event type, and adding annotation information to the output event text data. The present invention can reversely generate accurate and effective text data containing event pattern annotation information at low cost and high efficiency, and ensure the rationality and naturalness of the generated text data with respect to the event pattern and event structure.

The utility model discloses an environmental event structuring device based on adaptive baseline tracking. The device comprises a voltage follower, an operational amplifier, an integral switching network, an AND gate, a timing pulse generator, an inverter and a reset switch, an input signal is compared with a baseline voltage generated by the integral network through the operational amplifier, and the output of the baseline voltage and a timing pulse are subjected to logical operation in the AND gate to generate a self-adaptive control signal; after phase reversal by the phase inverter, the reset switch is controlled to quickly discharge the integrating capacitor, and the integrating switching network is controlled to switch the integrating time constant, so that closed-loop control is formed, and slow baseline tracking in a quiet period and quick reset response in an event period are realized; the device outputs three analog signals of baseline voltage, peak voltage and pulse width voltage in real time through closed-loop control of a hardware circuit, and original signal transmission load is reduced from the source.

A computer-implemented method of discovering a composite durational event structure through temporal logic includes identifying a plurality of temporally related atomic events from temporal data trajectories of a multivariate dataset according to a definition of an atomic event predicate. At least one composite event having a durational event structure of at least some of the plurality of the temporally related atomic events is discovered by machine learning. An action is performed that is selected from a predetermined list associated with the composite event.

The present invention discloses a progressive opinion extraction method and system for hot topics. The method is as follows: providing prior knowledge; constructing a seed event structure diagram based on the prior knowledge, where the diagram contains opinion information nodes and edges representing the relationships between opinion elements; combining the event structure diagram and data in the current stage to train and predict an opinion extraction model, and giving the prediction results of the data in the current stage after the training ends; removing the opinions that already exist in the event structure diagram, and submitting the new opinions to experts for confirmation; screening the confirmation results returned by the experts, removing the unqualified opinions, and adding the qualified opinions to the event structure diagram; returning to the opinion extraction step again, and repeating this cycle until the opinion extraction model converges. The present invention uses historical information for opinion extraction from new texts under the same topic, can effectively mitigate the impact of unbalanced hot topic datasets on neural models, and can obtain high-quality opinion information with a small amount of labeled data.

The invention is suitable for the technical field of document processing, and provides a document-level event element extraction method and system based on a pre-training language model.The method comprises the following steps that a document is loaded and preprocessed, and the document is segmented into a plurality of text segments through a sliding window method; a word segmentation device corresponding to the pre-training language model is used for marking the text segments, and the text is converted into a token sequence; inputting the token sequences into a pre-training language model, encoding each fragment, fusing the document-level global context, and determining the final representation of each token sequence; event element boundaries are recognized from the final representation of the token sequence, and element types are determined; and taking all the obtained elements as nodes, constructing an element graph, modeling the element graph through a graph neural network, and determining an event structure relationship. According to the method, the global semantics of the long document can be better modeled, the context information of the document can be deeply understood, and the event element extraction quality is improved.

The present invention provides a system and method for converting power notification text into 5G messages. The event parsing module receives raw power event data from the power PMS and DMS systems, adopts rule parsing and key field extraction algorithms, and outputs a standardized structure; the summary generation module receives structured event data, combines the event type and the target user portrait, and generates a popular text summary; the graphic generation module maps the geographic coordinates and device number in the event structure to the GIS platform, and highlights the event area with a hot zone on the GIS map; the graphic and text linkage module anchors the summary text and the graphic, corresponds the event range in the text to the graphic hot zone, and binds the event time to the estimated recovery time countdown; the message encapsulation module encapsulates the text summary and graphic content into a 5G rich media message format, and finally sends it to the user terminal through the operator's 5G core network.

The embodiment of the invention provides a data processing method and device. The method comprises the steps that a target event is converted into an initial event intermediate representation of a preset event structure; determining an event processing pipeline according to the task type corresponding to the target event; performing transformation processing on the initial event intermediate representation according to a plurality of transformation processing stages to generate candidate event intermediate representations; determining a target model according to the candidate event intermediate representation, and determining a rendering processing stage according to the candidate event intermediate representation and model configuration of the target model; and performing rendering processing on the candidate event intermediate representation according to the rendering processing stage, and generating a target event intermediate representation matched with the target model input format. Through the layered, configurable and dynamically adaptive context construction method, the problem of low context generation quality caused by model capability difference, long-range dependency loss, tool calling complexity and insufficient control constraint is solved, and the adaptability, reliability and execution efficiency of a complex agent system are improved.

The invention discloses a structured data intelligent extraction method based on multi-modal feature fusion. The method comprises the steps of multi-modal data acquisition, data primary processing, multi-modal fusion alignment, data analysis model construction and event structured representation acquisition. The invention relates to the technical field of public security event structured data intelligent extraction, in particular to a structured data intelligent extraction method based on multi-modal feature fusion, and the method comprises the steps: obtaining original data through data collection; a joint semantic field design is combined with a memory prototype retrieval mechanism, so that the semantic barrier problem among heterogeneous multi-source data is solved, and the stability of the model under partial mode missing or data noise interference is improved; a cascade residual decoder model is adopted as a data analysis model, and the overall consistency and accuracy of a final structured output result are improved by explicitly modeling the dependency relationship between tasks.

The invention relates to a data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: in response to a triggering operation for data modification of a document in a source database, obtaining a data modification log corresponding to the triggering operation, and generating event structure information corresponding to the data modification according to the data modification log; storing the event structure information into a target message queue, and under the condition that initial event structure information matched with the event structure information exists in the target message queue, combining the event structure information and the initial event structure information; and periodically obtaining event structure information corresponding to the source database in the target message queue according to a preset period, and updating a corresponding document in a target database according to the event structure information. The method can improve data synchronization efficiency and reduce resource consumption.

This application provides a method and system for extracting technical and economic risk events based on monitored entities, belonging to the field of entity extraction technology. The method includes: performing entity recognition on multi-source scientific and technological texts, comparing and filtering technical and economic monitoring entities, and outputting a candidate monitoring entity list; extracting semantic segments using the candidate monitoring entity list as anchors, and determining event types based on trigger word matching rules; performing dependency parsing and semantic role labeling on the trigger word set, constructing a standardized event structure, extracting semantic relationships, and outputting a risk event candidate structure set; identifying chapter-level main events, aggregating paragraph-level related events to form a master-slave event structure; assembling event chains based on the master-slave event structure, and performing standardized output. This application can solve the technical problem of poor reliability in the extraction of economic risk events in the prior art, achieving the technical effect of improving the reliability of extraction.

The application discloses a high-concurrency processor architecture based on an instruction-level event structure and a scheduling method thereof, is based on RISC-V instructions, and defines the stagnation, successful termination, sequential execution, conditional branching and merging operation of a program through a process algebra (PA-ISA) oriented to an instruction set architecture (ISA). On the basis of the PA-ISA, the dependence relationship between instructions in program execution is described through an instruction-level event structure (IES). The instruction-level event structure model is adopted to describe the dependence relationship between instructions in the program, the instruction concurrency is improved, and good expansibility is achieved. The high-concurrency processor architecture based on the IES is combined with an asynchronous circuit, an event triggering is taken as a basic execution advancing mode, the frequency or energy efficiency is improved, the bypass control mechanism in the out-of-order execution is simplified, and the system reliability is improved. The instruction-level event structure is combined with a double-path instruction fetching mechanism, the instruction waste and performance loss are reduced, and the fault tolerance capability under a large-scale instruction fetching strategy is optimized.

The application discloses a network attack path tracking method and system based on a three-domain communication event structure, relates to the technical field of network security, and comprises the following steps: converting the three-domain communication event structure into a heterogeneous graph structure composed of nodes and multi-dimensional label edges, and generating an industrial network topology graph; training a graph neural network model by using the industrial network topology graph, identifying abnormal jump paths and attack chain segments, and generating a suspicious path set; performing consistency calculation and weighted fusion on communication behaviors, protocol calling logic and physical state responses in the suspicious path set, and generating a credibility score vector; performing fusion calculation on the credibility score vector, selecting a path with the lowest credibility as a high-risk attack path, and combining a time sequence, the industrial network topology graph and an abnormal jump path to backtrack and reconstruct an attack path starting point, so that an attack propagation chain is obtained. The application improves the precision and efficiency of industrial network security situation awareness.

The embodiment of the specification provides a data processing method and device, the method comprises the following steps: converting a target event into an initial event intermediate representation of a preset event structure; determining an event processing pipeline according to a task type corresponding to the target event; performing transformation processing on the initial event intermediate representation according to a plurality of transformation processing stages to generate a candidate event intermediate representation; determining a target model according to the candidate event intermediate representation, and determining a rendering processing stage according to the candidate event intermediate representation and a model configuration of the target model; and performing rendering processing on the candidate event intermediate representation according to the rendering processing stage to generate a target event intermediate representation matched with a target model input format. Through this layered, configurable and dynamically adaptive context construction method, the problem of low quality of context generation caused by differences in model capabilities, loss of long-range dependencies, complexity of tool calls and insufficient control constraints is solved, and the adaptability, reliability and execution efficiency of a complex intelligent agent system are improved.

The present application provides a conflict and dispute incident early warning method, system, program product and storage medium, and relates to the field of information and communication technology specifically suitable for administrative, commercial, financial, management or supervisory purposes. The first feature data related to the subject information is extracted in the event structure tree using feature extraction rules, so that the key features of the event can be clearly presented. For personnel data, after constructing the personnel structure tree by word segmentation and part-of-speech tagging, the extracted words are subjected to sentiment tendency analysis, and negative sentiment words are marked, so as to facilitate subsequent judgment of the conflict and dispute incidents. The subject information and personnel are clustered according to the first feature data and the second feature data. The personnel carry the marked words during the clustering process, so that the event is closely associated with the relevant personnel, and the deep integration of data is realized. The problem of data confusion and mismatch is solved, so as to judge the real situation and development trend of the conflict and dispute incidents and improve the accuracy of the early warning.

This invention discloses a real-time scheduling method and system based on the Wayland protocol, relating to the field of graphics display based on the Wayland protocol. The method includes the following steps: adding the `priority` keyword to all client-side event structures in the server; constructing the `wlr_scheduler` protocol; assigning different scheduling strategies to clients based on the binding status of the `wlr_scheduler` protocol; when processing epoll events on the server, placing client-side events into high-priority or low-priority queues according to different scheduling strategies, and sorting client-side events within the same queue according to the `priority` keyword; scheduling client-side events in a manner that prioritizes processing client-side events in high-priority queues and processes client-side events in low-priority queues later. Clients only need to register the `wlr_scheduler` protocol to request the activation of real-time scheduling, without modifying system configuration files or executing complex commands, improving deployment efficiency and ease of use.

The application discloses a kind of structured data intelligent extraction method based on multi-modal feature fusion, method includes multi-modal data acquisition, data preliminary processing, multi-modal fusion alignment, data analysis model construction and obtains event structured representation.The application relates to the technical field of public safety event structured data intelligent extraction, specifically refers to a kind of structured data intelligent extraction method based on multi-modal feature fusion, the original data is obtained by data acquisition;Using joint semantic field design combined with memory prototype retrieval mechanism, solve the semantic gap problem between heterogeneous multi-source data, at the same time, the stability of the model under the condition of partial modal loss or data noise interference is improved;Cascade residual decoder model is used as data analysis model, the overall consistency and accuracy of the final structured output result are improved by explicitly modeling the dependency between tasks.