503 results about "Information transformation" patented technology

The invention discloses a retrieval enhancement generated document screening system and method fusing a verification mechanism, and relates to the technical field of document screening, the system comprises a user input and query analysis module for extracting key information through natural language processing, and converting the key information into a high-dimensional semantic vector, a meta-tag and a keyword set; the multi-source document retrieval module is used for obtaining documents from multiple data sources through mixed retrieval and generating a candidate set through preliminary screening and sorting; the credibility evaluation and security verification module is used for generating scores and labels after multi-dimensional evaluation and screening qualified documents; the document consistency detection module is used for detecting document conflicts, processing and sequencing, and ensuring logic consistency; the document acquisition and generation module is used for inputting qualified documents into a generation model and generating answers with references; and the result output and tracing module is used for outputting answers and recording whole-process data to ensure traceability. The invention aims to ensure the accuracy and credibility of the generated content through a multi-dimensional verification mechanism.

The invention relates to an intrusion detection method based on cross-domain security management and a shared behavior model. The method comprises the following steps: acquiring multi-dimensional original data according to a preset cross-domain data acquisition rule and multi-domain node deployment; performing compliance, integrity and format matching degree verification on the original data, shielding sensitive information by using a dynamic desensitization technology based on a verification result, converting a heterogeneous data format, filtering missing field abnormal data, and obtaining compliance data; the method comprises the following steps: extracting a multi-dimensional feature set of user cross-domain access, constructing a shared behavior feature vector through weighted calculation, constructing a reference behavior model library in combination with a cross-domain security policy, and screening out intrusion behaviors and feature deviation data through feature comparison and behavior deviation calculation; according to the method, cross-domain security audit logs are fused for correlation analysis, intrusion behavior types and risk levels are judged by means of a Bayesian network model, differential security response strategies are generated and executed, and cross-domain intrusion detection and protection are achieved.

The invention discloses a Web automatic testing method, system and device, a medium and a program product, and belongs to the technical field of artificial intelligence. The method comprises the steps that test case abstract representation information is generated according to interactive input of a user and a test case mapping template, and the test case abstract representation information comprises a target test task type indicated by the interactive input and intention natural language description information; based on the test case abstract representation information, obtaining a target screenshot of the tested Web page and attribute information of interaction elements; a multi-mode large language model is called to conduct reasoning based on the target screenshot, the attribute information of the interaction elements and the intention natural language description information, reasoning result information is output, and the reasoning result information represents operation executed on the target interaction elements located at the target position in the tested Web page; and converting the reasoning result information into a machine executable instruction, and executing the machine executable instruction. According to the embodiment of the invention, the stability of Web automatic testing can be improved.

The invention is suitable for the field of traditional Chinese medicine quality control and analysis technology improvement, and provides a traditional Chinese medicine fingerprint spectrum intelligent decision-making system and analysis method based on artificial intelligence, and the method comprises the steps: S1, obtaining one-dimensional fingerprint spectrum data information of a large number of traditional Chinese medicine samples through a plurality of analysis technologies; s2, converting the acquired one-dimensional fingerprint spectrum data information into a two-dimensional time-frequency matrix by using adaptive noise complete set empirical mode decomposition-Hilbert-Huang transform; s3, inputting the obtained two-dimensional time-frequency matrix into a pre-trained multi-mode deep learning model, dynamically optimizing model parameters through a model agnostic element learning framework, and outputting traditional Chinese medicine quality evaluation, authenticity identification and origin traceability results; and S4, writing the decision result into a block chain evidence storage system to generate a non-tampering quality tracing record. The deep learning model can effectively process complex data, identify subtle modes and manage baseline drift, peak overlapping and other problems, so that more reliable fingerprint analysis is realized.

The invention relates to the technical field of data processing, in particular to a fault repair method and system based on big data analysis. The method comprises the following steps: in response to a received new repair request, obtaining a state deviation degree based on a difference between a real-time operation parameter and each type of historical operation parameter; converting the text information in the new repair request into a real-time fault vector, and calculating the semantic similarity between the real-time fault vector and the historical text vector of each fault type; for any fault type, performing weighted fusion on the state deviation degree and the semantic similarity corresponding to the fault type to obtain a comprehensive evaluation index of the fault type, and determining the fault type with the highest evaluation index as a diagnosis result of current repair; and according to the diagnosis result, intelligent order sending is carried out on the repair task. The method has the effects of improving the maintenance timeliness and improving the human resource utilization rate.

The invention relates to a knowledge base construction method and system for multi-source heterogeneous files, and the method comprises the steps: receiving Word, PDF, Excel and other multi-source heterogeneous files, and converting the multi-source heterogeneous files into standardized representation through a file analysis function; an event boundary recognition technology fusing rule matching, entity recognition, semantic similarity and large language model verification is adopted, and a cross-paragraph complete business event is accurately extracted; generating structured information through an information extraction function; the information is converted into vectors, full-text indexes and a graph database to be stored by means of a multi-dimensional storage conversion function; and verifying and correcting an extraction result through a quality auditing function, and finally outputting a knowledge base containing an event set, an entity relationship and vector representation. According to the method, the problem of knowledge fragmentation in traditional document processing is effectively solved, and the consistency, the searchability and the reasonability of knowledge are remarkably improved.

The invention relates to the technical field of artificial intelligence, and discloses a marketing knowledge base construction method, device and equipment based on artificial intelligence, and the method comprises the steps: obtaining basic information and session information, and converting the session information into text data according to the basic information; analyzing implicit relation data among the employees, the products and the clients based on the basic information, and extracting marketing knowledge from the text data; and carrying out hierarchical classified storage on the implicit relation data and the marketing knowledge, and pasting multi-dimensional labels on different knowledge to form a marketing knowledge base. According to the invention, through integration and structured processing of multi-source data, potential association among employees, products and clients is mined, and actual marketing knowledge is accurately extracted; hierarchical storage enables a knowledge system to be clearer, and multi-dimensional labels improve retrieval efficiency; the dynamic updating mechanism ensures the timeliness of knowledge, provides accurate knowledge support for a marketing scene, assists employees to quickly match verbal skills and schemes, and improves the communication efficiency and the transaction rate.

The invention discloses a robot and an intelligent interaction method thereof, and relates to the technical field of robots, and the robot comprises an instruction obtaining module which is used for converting external instruction information into text information; the artificial intelligence module is used for performing vectorization processing and similarity comparison on the text information and keywords in a preset task list through a large model to obtain a conventional target task and an unconventional target task; the task decomposition module is used for decomposing the conventional target task or the unconventional target task into a plurality of sub-tasks and determining solutions matched with the sub-tasks according to the types of the sub-tasks; the task execution module is used for supervising and controlling execution of each subtask; the memory module is used for storing key data and a knowledge graph database in the execution process of each subtask; and the planning decision module is used for controlling the operation of the modules. According to the invention, man-machine interaction and autonomous planning and intelligent control of the robot body can be realized.

The invention provides a knowledge graph generation method and system combined with dynamic semantic association mining in the technical field of artificial intelligence and knowledge engineering, and the method comprises the steps: S1, collecting basic data which is used for generating a knowledge graph and comprises relational data and non-relational data, and carrying out the preprocessing of each basic data through a kettle tool; s2, reasoning each piece of basic data through a LangChain framework in combination with a large model so as to dynamically and semantically associate and mine ontology information from each piece of basic data; s3, initializing a knowledge graph, converting the ontology information into a graph structure of the knowledge graph, and dynamically updating the knowledge graph based on the newly mined ontology information; and step S4, storing the knowledge graph in a graph database Neo4j in real time, and performing visual display on the knowledge graph stored in the graph database Neo4j through a Neo4jBLOOM tool. The knowledge graph generation method has the advantages that the flexibility, the automation degree, the efficiency, the semantic consistency, the dynamic adaptability and the expansibility of knowledge graph generation are greatly improved.

The invention provides a railway vehicle production line digital twin system and method, and the system comprises a physical space layer which is used for obtaining the state information of a railway vehicle physical production line in real time; the information layer is used for performing information conversion and analysis on the state information of the railway vehicle physical production line to obtain processed railway vehicle production line information; and the virtual space layer is used for updating the railway vehicle virtual production line model based on the processed railway vehicle production line information, so that the railway vehicle virtual production line model corresponds to the railway vehicle physical production line. Through the digital twinning technology, digital transformation of the railway vehicle manufacturing industry is promoted, the production efficiency is improved, quality control is optimized, the maintenance cost is reduced, and the production flexibility is enhanced.

The invention discloses an automatic operation and maintenance system based on fusion of an AI agent and a configuration management database, and the system comprises a data collection module which is used for automatically collecting configuration information of IT infrastructures through a multi-mode collection technology; the configuration management database is used for converting the configuration information into configuration items and dependencies to construct a knowledge graph; the AI agent comprises a log analysis unit used for carrying out structured processing on the unstructured log data; the anomaly detection unit is used for carrying out anomaly detection on the structured log data and time sequence index data by adopting an unsupervised machine learning algorithm; the root cause positioning unit is used for performing topological relation reasoning on the detected abnormal events based on a knowledge graph, and determining a fault type and a root cause configuration item causing the fault; and the automatic executor is used for calling an automatic operation and maintenance tool to execute repair operation according to the fault type and the root cause configuration item. The operation and maintenance efficiency can be improved, and the fault repair time can be shortened.

The invention discloses a long-distance maneuvering path planning method and system fused with DOP information, and belongs to the technical field of path planning and navigation. The method comprises the following steps: collecting special vehicle information, GNSS DOP information, geographic information and traffic information; based on the DOP value and the traffic condition, the roads are preliminarily screened, and the gradient, the slope direction, the height limit, the load bearing, the turning radius and DOP information are integrated; road condition information is converted into constraint conditions, and DOP information serves as an optimization target and is fused into a heuristic cost function of an improved algorithm; a path with the best navigation effect is obtained through path searching, visual display is carried out on a geographic information system map, and DOP information changes of all key points on the path are displayed in real time. According to the method, a GNSS signal blind area can be effectively avoided, the feasibility and navigation precision of path planning are improved in combination with vehicle dynamics constraints, and the method is suitable for long-distance maneuvering tasks of special vehicles.

The invention provides a demand specification generation method and system based on multi-modal understanding, and relates to the field of artificial intelligence, and the method comprises the steps: carrying out the content understanding operation of data of each modal through employing a corresponding content extraction tool, so as to generate a demand representation document after multi-modal unification; establishing a demand knowledge base according to an existing template base and a corresponding rule base, matching and comparing the demand knowledge base with the demand representation document, checking the integrity of the demand representation document, and generating a question for seeking a decision; creating an overall framework of the standard document according to the standard standard template, and performing content filling on the overall framework according to the demand representation document and an answer to the question seeking the decision to generate the standard document; and collecting feedback information for the standard document, analyzing the feedback information by using a large language model, and converting the feedback information into executable modification suggestions for the standard document. According to the method, the automation degree, the integrity and the accuracy of demand specification generation are improved.

The invention discloses a webpage vulnerability identification method and device, electronic equipment and a program product, and relates to the technical field of artificial intelligence, and the identification method comprises the following steps: obtaining a page structure and interface information of a target page; performing feature extraction on the page structure to obtain a target vector, converting the interface information into a text sequence, and performing feature extraction on the text sequence to generate an interface semantic feature vector; the target vector and the interface semantic feature vector are input into a preset multi-modal model, a vulnerability attack request is generated, and the vulnerability attack request corresponds to response data; and performing semantic recognition on the response data by adopting a preset language model to obtain a vulnerability recognition result of the target page. According to the invention, the technical problem of low vulnerability identification accuracy in related technologies is solved.

The invention belongs to the field of big data processing, and particularly relates to an event analysis method, device and equipment and a storage medium, target event information is obtained, the target event information is converted into event feature vectors, the event feature vectors are input into multiple analysis models respectively, and the analysis models output corresponding event types and initial risk levels respectively. Performing similarity matching on the event feature vector and a historical event feature vector of a historical event in a preset knowledge base, screening one or more pieces of historical event information of which the similarity score is greater than a preset threshold, and determining the credibility of each analysis model based on the historical event information and the event type, performing weighted fusion on the initial analysis result based on the credibility of each analysis model, and determining a target risk level corresponding to the target event information; according to the method, by combining multi-model analysis, historical data similarity matching and credibility weighted fusion, the accuracy of risk level judgment of the target event is improved.

The invention relates to the technical field of chip design, and provides a clock constraint generation method, electronic equipment and a storage medium, and the method comprises the steps: building a relational database based on hierarchical design information of a chip, the relational database comprising an instantiated module relationship in the chip and a cross-module port connection relationship; determining a clock source from the relational database, and traversing a propagation path of the clock source in the relational database by taking the clock source as a starting point; and generating a clock constraint file of the chip based on the propagation path of the clock source. According to the method, the electronic equipment and the storage medium provided by the invention, the hierarchical design information is converted into the dynamic, queriable and traversal relational database, so that the clock propagation path is reconstructed, the clock constraint file is driven to be automatically generated, and on the premise that the complete hierarchical design information is reserved, the automatic generation of the clock constraint file is realized. The efficient, accurate and complete propagation path reconstruction is realized, and the clock constraint generation efficiency and accuracy are improved.

Device for the intelligent encapsulation of legacy data information systems with the integration of artificial intelligence, comprising: a collection unit for legacy interfaces, configured to intercept communication data from existing platforms; a semantic interpretation unit designed to analyze and map data structures and process semantics; a contextual abstraction layer designed to convert interpreted information into standardized, interoperable formats; a policy-driven management module that ensures secure access, Data transformation and regulatory compliance are ensured; and a learning and inference unit for adaptive optimization of data mappings and operational logic.

The invention provides an information visualization method and system, a medium, equipment and a program product, and relates to the technical field of information processing, and the method comprises the steps: obtaining heterogeneous input information; performing category detection on the heterogeneous input information by utilizing the classification model, and determining a category corresponding to the heterogeneous input information; calculating entity relevancy, information relevancy and information weight corresponding to the heterogeneous input information according to the category; inputting structured label information corresponding to the heterogeneous input information according to the entity relevancy, the information relevancy and the information weight; constructing an atlas data structure corresponding to the structured label information; and mapping the map data structure into visual elements to obtain visual information. According to the method, heterogeneous input information is converted into visual information, so that leap-type improvement from bottom-layer data quantification to top-layer cognitive perception is realized.

The invention relates to the technical field of intelligent medical treatment, and discloses a three-level medical network intelligent referral method and equipment, and the method comprises the steps: collecting patient diagnosis and treatment information and medical institution resource information, and converting the information into structured data in a unified format; inputting the structured data into a preset referral decision model, carrying out correlation analysis on the illness condition severity feature of the patient and the medical institution reception capability feature, and generating a referral necessity evaluation result; when the referral necessity evaluation result indicates that referral is needed, performing comprehensive scoring on candidate receiving mechanisms in the structured data based on a multi-dimensional matching rule, screening out a target receiving mechanism according to a scoring result, and generating a referral suggestion scheme; and analyzing the referral suggestion scheme to construct a referral execution instruction, planning a transfer path in response to the referral execution instruction, and locking medical resources of the target receiving mechanism by using an intelligent contract mechanism to obtain a referral result. The referral efficiency of the medical network is improved.

The invention provides a control method and device for a multi-heat-source heat supply system. The control method and device can be applied to the technical field of intelligent heat supply. The method comprises the following steps: performing nonlinear conversion on initial prediction characteristics obtained by performing gating processing on respective characteristic sequences of meteorological information and previous load information of a building to obtain load prediction information of a heat supply system, and performing fusion processing on node information, branch pipe information and respective constraint conditions in previous operation information of a heat supply pipe network to obtain load prediction information of the heat supply system; water and heat distribution information of the heat supply pipe network is obtained; on the basis of the load prediction information, the hydrothermal distribution information and a target function, start-stop combination information and load distribution information of the multiple heat supply devices in the target time window are determined, and the target function is determined by energy cost information, load fluctuation information of the heat supply devices and start-stop times; and converting the start-stop combination information and the load distribution information into a control instruction and sending the control instruction to execution equipment so as to carry out heat supply control on the heat supply system.

The invention discloses an intelligent query method and system suitable for a large language model, and belongs to the field of artificial intelligence technology and natural language process.The method comprises the steps that consultation information is converted into corresponding question vectors, and related document fragments are retrieved from an external knowledge vector database; key information is extracted from the consultation information in combination with the large language model and the document fragments; on the basis of a Prompt self-optimization framework, generating a prompt word adaptive to the current service scene according to the scene information; and generating an SQL statement according to the key information and the cue word to query and output answer information. Key information of consultation questions can be understood, and correct consultation data can be conveniently output subsequently; on the basis of a Prompt self-optimization framework, the prompt word adaptive to the current service scene is generated according to the scene information, so that the accuracy of generating an actual service data query SQL statement can be improved; the SQL statement is generated according to the key information and the cue word so as to query and output the answer information, and the requirement of question consultation can be met.

An apparatus 100 for protecting privacy in a cloud-based data processing system 126 that uses Large Language Models, LLMs, (128, 216A, 216B) to process data is provided. The apparatus includes a receiver 110, a converter (112, 206A, 206B), a replacer 116, and a sender 120. The receiver is configured to receive personal and sensitive information to be sent to the cloud-based data processing system. The converter is configured to convert the received personal and sensitive information into pseudonyms by generating pseudonyms corresponding to the received personal and sensitive information. The replacer is configured to replace the received personal and sensitive information with the generated pseudonyms. The sender is configured to send the generated pseudonyms to the cloud-based data processing system for processing using the LLMs.

The invention discloses a vehicle refitting scheme generation method and system based on a large model and a knowledge graph, and relates to the technical field of electric vehicle networking, and the method comprises the steps: inputting an obtained user refitting demand text into a cloud large model, analyzing the refitting demand text, extracting key information, converting the key information into a query vector, and sending the query vector to a cloud server; the method comprises the following steps: establishing a vehicle refitting knowledge graph, performing matching retrieval with entity embedding in the commercial vehicle refitting knowledge graph, constructing cue words according to the retrieved knowledge, generating a vehicle refitting scheme through cloud big model thinking chain reasoning, calling a 3D component to render a scheme effect graph, and feeding back the scheme effect graph to the local; vehicle data, accessory data, scene data, law and regulation data and historical modification case data are obtained in advance, after data preprocessing, entities and relationships are obtained through named entity recognition and relationship extraction, a commercial vehicle modification knowledge graph is constructed, and entity embedding in the knowledge graph is obtained through graph neural network learning. According to the invention, a refitting scheme which better meets user requirements can be obtained.

The invention discloses a method and system for constructing a universal digital twin asset data model for multi-source heterogeneous data exchange and sharing, and belongs to the technical field of digital twin. The method comprises the following steps: obtaining three-dimensional data structures and three-dimensional data indexes of different geometric forms in a digital twin model, the spatial topological relation between the three-dimensional data structures is identified; converting texture map information of the three-dimensional data structure into a unified format, normalizing coordinates of the texture map information, and unifying vertex coloring information of the three-dimensional data structure to a standard color space; and performing material analysis and description on different material characteristics of the digital twin model, dynamically calling node objects corresponding to the different material characteristics to obtain real material information, and finally dynamically outputting to obtain a general three-dimensional data model. According to the invention, the problem that a unified digital twin floor scene is difficult to generate due to different sources and structures of current model data can be solved.

The invention discloses a measuring point table matching method, device and equipment and a medium, and belongs to the technical field of intelligent cabins of ships. The method comprises the following steps: acquiring a to-be-matched measuring point table, and converting to-be-matched measuring point information in the to-be-matched measuring point table into a first vector; acquiring a plurality of second vectors according to a preset standard measuring point vector database; calculating the similarity between the plurality of second vectors and the first vector, and determining a first candidate set based on the similarity; reordering the first candidate set based on semantic correlation to determine a second candidate set; and performing reasoning matching on the second candidate set through the large language model, and determining a matching result in the second candidate set. According to the method, the matching accuracy is improved by means of semantic analysis, the method does not need to depend on a predefined rule through a large language model, the method has the universality of adapting to ship intelligent cabin systems and comprehensive monitoring systems developed by different manufacturers, and the problem that in the related technology, it is difficult to consider high efficiency, accuracy and universality at the same time in measuring point matching is effectively solved.

The embodiment of the invention provides a sensitive data detection method, a related device and a medium. The method comprises the following steps: acquiring to-be-detected data; a double-encoder rule generation model is called to convert the user query instruction into first vector data, text information of a knowledge source library is converted into second vector data, target knowledge text information is determined according to the first vector data and the second vector data, and the knowledge source library at least comprises one of a law and regulation library, an industry word library and an enterprise database; calling a dual-encoder rule generation model to generate a first detection rule according to the templated instruction and the target knowledge text information; calling a large language model to carry out adaptive optimization on the first detection rule to obtain an optimized second detection rule; and calling the multi-mode joint detection model to perform sensitive data detection on the to-be-detected data according to a second detection rule to obtain a sensitive data detection report. The embodiment of the invention aims to improve the accuracy and timeliness of sensitive data detection.

The invention relates to the technical field of AR remote operation and maintenance, and provides an operation and maintenance system, an operation and maintenance terminal, an expert terminal, a server and a control method thereof, and the operation and maintenance system comprises an operation and maintenance unit which is used for collecting video information and depth data of a physical environment in real time; establishing a mapping relation between the physical environment and the virtual coordinate system according to the video information and the depth data of the physical environment to obtain a physical environment grid and a camera projection matrix; the expert unit is used for intercepting a static frame picture and generating marking information after selecting a marking type; the operation and maintenance unit is used for receiving the marking information and the marking type in real time; converting the labeling information into a camera space ray through the camera projection matrix; calculating a collision point of a camera space ray and the physical environment grid, and determining a three-dimensional space coordinate; and rendering the corresponding three-dimensional marking model in the display field of view of the operation and maintenance unit. The method is used for realizing remote maintenance of IT equipment, mapping expert guidance information to a physical environment and carrying out augmented reality visual display.

The invention provides an industrial material dialogue type recommendation method and system based on a large model and ElasticSearch, search recommendation of industrial materials is enabled by using a large language model, and a material information conversion model based on the large language model is introduced on a traditional search engine ElasticSearch. According to the method, user material requirements in a natural language form are understood, material keywords and material performance parameter information are inferred, and then search is performed from ES, so that appropriate materials can be recommended to the user, and the appropriate materials can be recommended to the user in a multi-round natural language dialogue form; and a reinforcement learning method based on user feedback and user interaction behaviors is adopted to continuously optimize a material information conversion model based on a large language model, so that the understanding ability of the model on implicit intentions of users and the inference ability on key parameters are stronger and stronger, and the correlation and accuracy of recommendation results are greatly improved.

The invention provides a social media data-driven urban ponding depth inversion and precise positioning method. The method comprises the following steps of: 1, capturing and preprocessing multi-source social media data; step 2, performing ponding depth inversion based on image recognition; 3, accurately positioning the ponding position based on the text and the large model; extracting character information in pictures and videos by means of a picture character recognition technology in a large model, recognizing typical buildings therein, and assisting in positioning a flood position; screening out effective place information and time data related to ponding by adopting a large model; the identified location information is converted into specific location coordinates and detailed addresses by combining a geocoding technology, so that high-precision positioning is realized; and 4, outputting a comprehensive result: generating structured disaster information, and supporting direct calling of an emergency platform. Through combination of social media data and a space-time distribution model, ponding depth inversion is realized, quantitative data of the ponding depth is acquired, a disaster site is rapidly positioned, and decision making and flood control and disaster relief work are supported.

The invention relates to the technical field of medical data processing, and particularly provides a medical data quality control rule automatic generation method and system, a terminal and a medium, and the method comprises the steps: obtaining medical data, marking correct data and wrong data in the medical data, and carrying out the feature extraction of different types of medical data, and obtaining corresponding feature vectors; standard medical information of the data is obtained, and the standard medical information is converted into natural language cue words; after fine tuning training is carried out on the large language model, a corresponding quality control rule is output, and the validity of the quality control rule is evaluated based on correct data and wrong data; the method comprises the steps of screening out error data in medical data based on an existing quality control rule, obtaining an error mode of the error data through a clustering algorithm, matching the error mode with the existing quality control rule, and judging whether a quality control rule needs to be newly added or not based on a matching result. A comprehensive and effective medical data quality control system is constructed, and the medical data quality and accuracy are improved.