704 results about "Information transformation" patented technology

Techniques for using a model to generate a response to a user input, where the response is associated with a personality determined to be relevant to the user input, are described. The system receives a user input and context data associated with the user input. Using the user input data and / or the context data, the system determines a personality (e.g., including a personality type and / or personality characteristics) relevant to the user input. The system generates a prompt instructing a model to generate a response to the user input that corresponds to the personality. The model processes the prompt to generate a response to the user input that corresponds to the personality. In some embodiments, the model generates a request for another component of the system to generate information responsive to the user input. The model may transform the responsive information into the personality-associated response.

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 discloses a cross-platform equipment alarm information acquisition method, and particularly relates to the field of information acquisition, the method adapts to different platform equipment through a standardized interface layer, the interface layer comprises an equipment connection protocol library and a unified data conversion unit, and an original log of the equipment is analyzed in real time based on a preset alarm rule template; extracting key information and generating an alarm event object; converting the alarm key information into an alarm event in a unified format, and adding equipment identification metadata; alarm events are asynchronously transmitted to a central processing server by utilizing a high-reliability message queue, and the transmission reliability is guaranteed by adopting various mechanisms; performing duplicate removal, priority classification and persistent storage on the alarm events in the central server, and ensuring data consistency by adopting a hierarchical storage architecture; the whole processing link is provided with perfect monitoring indexes, and automatic capacity expansion and contraction are achieved.

The invention provides a dynamic rule combination-based data query method and apparatus, and an electronic device.The method comprises the steps of firstly obtaining query parameter information input by a user, and then analyzing fields, operators and values in each query parameter group; based on the analyzed fields, operators and values, a corresponding target processing rule is matched for each query parameter group from a preset processing rule set, and then the query parameter group is processed according to the corresponding target processing rule for each query parameter group; and generating an SQL query statement based on a preset logic operator set and a processing result of each query parameter group, and finally executing the SQL query statement to query the database to obtain a database query result. By adopting the method and the device, the query parameter information can be automatically converted into the SQL query statement, the operation complexity of multi-condition complex query can be reduced, and meanwhile, the universality of the multi-condition complex query in diversified query scenes is improved.

The invention relates to a quadruped robot path planning method fusing visual semantic information and a laser radar. The method comprises the following steps: acquiring environment data, wherein the environment data comprises key ground semantic information, a depth image and original laser radar point cloud information; converting the key ground semantic information into laser radar key ground semantic point cloud information based on the depth image, and performing spatial fusion on the laser radar key ground semantic point cloud information and original laser radar point cloud information to obtain multi-source point cloud fusion information under a unified reference system; the multi-source point cloud fusion information is preprocessed, and non-ground interference points are filtered out; constructing a semantic enhanced local path planning model based on a semantic penalty term and a dynamic window path planning algorithm; on the basis of the feasible speed of the quadruped robot, the preprocessed multi-source point cloud fusion information and a semantic enhanced local path planning model, feasible trajectory selection is carried out, and an optimal obstacle avoidance planning path is determined. And the navigation safety and the task execution efficiency of the robot in a high-risk industrial environment are remarkably improved.

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.

A computer-implemented method for controlling a robot collaborating with a human in an environment of the robot comprises: obtaining, by at least one sensor, multimodal information on the environment of the robot including information on a human acting in the environment; converting, by a first converter, the obtained multimodal information into text information; estimating, by an intent estimator, an intent of the human based on the text information; determining, by a state estimator, a current state of the environment including the human based on the text information; planning, by a behavior planner, based on the current state of the environment and the estimated intent of the human, a behavior of the robot including at least one multimodal interaction output for execution by the robot, and generating control information including text information on the at least one multimodal interaction output; converting, by a second translator, the generated text information into multimodal actuator control information; and controlling at least one actuator of the robot based on the multimodal actuator control information.

Methods and systems for interacting with users via a chatbot. A natural language query is received and processed by submitting a search query to a search engine. The search engine identifies relevant information including textual information and images for formulating a response. The identified information and query are submitted to a Large Language Model which generates a response displayed via the chatbot. The response may include textual information and relevant images. The system can extract text from images of documents and convert textual information into numerical vector representations for processing. Selectable options based on clustered relevant information can be provided to users for query refinement when appropriate. The chatbot interface enables natural language interactions while leveraging search capabilities and Artificial Intelligence to provide informative and helpful responses with both text and visual elements.

The invention belongs to the technical field of case information extraction, and particularly relates to a case information extraction system based on an AI large model, which comprises an input module, a processor, an AI screening model, a case database and a display, the processor is connected with the AI screening model, the processor converts input case information into an instruction recognized by the AI screening model, the AI screening model is connected with the case database, and the AI screening model carries out case screening in the case database based on the instruction. Cases of a patient are stored in a case database, the cases in the case database are browsed and screened based on an AI screening model, medical record texts are pre-trained based on a large-scale pre-training language model, then fine adjustment is carried out on a specific medical record data set, and by means of the powerful language understanding ability of the model, the medical record data set can be obtained. And the accuracy and recall rate of named entity recognition are 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 the technical field of human resource information management, in particular to a human resource information management system based on big data. The system comprises a matching combination unit, an evaluation filtering unit, an evaluation sorting unit and a credibility verification unit. The conversion and combination module carries out keyword matching scoring by utilizing post demand keywords and resume information, converts the resume information and the post demand information into semantic vectors of the resume information and semantic vectors of the post demand information through a pre-training language model, and then combines the semantic vectors with a similarity calculation function Similarity. According to the method, whether appropriate job seekers can be preliminarily screened out from the human resource information management library or not is judged, the defect of keyword matching can be overcome and the misjudgment rate can be reduced through the score of the semantic vector similarity, the situation that potential appropriate job seekers are missed due to the limitation of keyword matching is avoided, and the recruitment efficiency is improved.

The invention discloses an intelligent document analysis and question-answering method and system based on an RAG and a multi-modal knowledge graph, and aims to solve the problems that the existing GraphRAG mainly depends on text retrieval and generation, and lacks utilization of images or other modal information, so that the comprehensiveness and accuracy of answers are limited in a complex application scene. Analyzing the multi-modal document to obtain text modal information and image modal information; converting the text modal information into a text knowledge graph, and converting the image modal information into an image knowledge graph; fusing the text mapping knowledge domain and the image mapping knowledge domain to obtain a multi-modal mapping knowledge domain; and sequentially inputting the multi-modal knowledge graph into the embedded model and the vector database to obtain an entity vector database. And sequentially inputting a to-be-queried question of a user into the embedded model and the vector database to obtain information corresponding to the to-be-queried question, inputting the information corresponding to the to-be-queried question into the large language model, and outputting an answer to the to-be-queried question. The invention belongs to the field of data processing.

A method may include receiving, from an external entity, information associated with a procedure that includes a control representing a security policy. The method may include transforming the information into transformed information. The method may include determining, using a first machine learning model, a plurality of features including an average reconciliation ratio and an indication of whether the security policy is accurate, based on the transformed information. The method may include determining, using a second machine learning model, a probability that the transformed information does not satisfy a plurality of criteria, based on the plurality of features. The method may include determining whether the probability is greater than a threshold value, and upon determining that the probability is greater than the threshold value, determining, using a third machine learning model, a recommendation to implement one or more actions associated with the control, based on the probability.

The embodiment of the invention provides a software object processing method and device, equipment and a storage medium. In response to an editing operation on a first software object, converting the state information of the first software object into set structured data; executing the editing operation on the structured data to obtain the edited structured data; and generating an edited first software object based on the edited structured data. According to the software object processing method provided by the embodiment of the invention, the software object is controlled by executing the editing operation on the structured data of the software object, the use scene of the software object is widened, and the consistency and correctness of the editing operation can be ensured.

The invention provides an intelligent file handling guiding method and device, electronic equipment and a storage medium, relates to the technical field of self-service, is applied to a consultation file handling guiding robot interaction system with a built-in large language model LLM, and extracts a guiding word and a data analysis rule of a corresponding item from a business management platform according to an obtained item name; injecting the guide word into a cue word of a large language model LLM, performing closed domain dialogue with a user based on the large language model LLM, and guiding the user to provide necessary file handling information until the necessary file handling information is complete; and converting the necessary file handling information into a data format consistent with a business handling system according to the data analysis rule, automatically filling the data format into the business handling system, and displaying a file handling information filling result to a user. Therefore, through intelligent guidance of multiple rounds of conversations with the user and automatic data analysis and filling, the file handling efficiency is improved, and the user experience is enhanced.

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 relates to an intelligent inquiry and risk evaluation method for gynecological tumors. The method comprises the following steps: acquiring symptom information of a consultant and tumor medical history information of relatives in a plurality of generations of families of the consultant; constructing a tumor genetic family diagram by using the tumor medical history information, and then evaluating genetic risks of consultants to generate genetic consultation suggestions; constructing a symptom semantic network based on a medical ontology, and converting the symptom information into standard symptom data; calling a corresponding hierarchical inquiry protocol according to the standard symptom data to generate an intelligent diagnosis result; and integrating the genetic risk assessment result and the intelligent diagnosis result and outputting a diagnosis suggestion. Gynecological tumor inquiry consultation and risk evaluation can be automatically completed, and meanwhile a clinical research form is generated and inserted into a hospital electronic medical record system. The whole process does not need manual operation of doctors, the workload of information collection and input of the doctors is greatly reduced, and the doctors can concentrate on the core diagnosis and treatment process.

The invention belongs to the field of workshop scheduling, and particularly discloses a product process planning and workshop collaborative online scheduling method and system considering random arrival of workpieces, and the method comprises the steps: converting a dynamic integrated process planning and workshop scheduling problem into a Markov decision process, and converting workpiece process information into an OR description matrix; performing reinforcement learning training on the deep neural network of the intelligent agent based on a Markov decision process; during training, at each decision point, if there is a random arrival workpiece, the process information of the workpiece is converted into an OR description matrix and workshop information is updated; secondly, determining a workshop feature vector according to the workshop information, making a scheduling decision by an intelligent agent according to the workshop feature vector, optimizing deep neural network parameters according to a reward function, and updating the workshop information; and realizing product process planning and workshop collaborative online scheduling based on the trained intelligent agent. Real-time and efficient operation of the production scheduling system can be guaranteed, so that the production line keeps continuous and stable operation, and the production efficiency is improved.

The invention provides a method and device for realizing image detection based on computing power of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructures, and the method comprises the steps: S1, obtaining a first image; s2, identifying a first area where a first object indicated by the input first keyword is located in the first image; s3, acquiring information of the first area, and converting the information of the first area into first area information in a target format; s4, establishing a corresponding relationship between the first category information to which the first object belongs and the first region information; and S5, training a target detection model by using the first category information, the first region information and the corresponding relationship, wherein the target detection model is used for realizing image detection based on the computing power of the intelligent computing center. The trained target detection model is obtained in the above mode, and image detection is performed by using the target detection model based on the computing power of the intelligent computing center, so that the detection precision can be 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.

Systems and methods provide for automating the conversion of email orders into structured order entries using generative AI, leveraging an integrated architecture comprising a Real-Time Data Mesh (RTDM), Advanced Analytic and Machine Learning (AAML) Module, and Single Pane of Glass (SPoG) User Interface. The system includes an Email Parser that extracts order information from emails, an Order Generation Engine that converts this information into structured entries, and an Integration Gateway that synchronizes the entries with external systems. The RTDM manages data flow and transformation, while the AAML provides predictive analytics and process automation. The SPOG UI performs real-time data visualization and user interaction. The system enhances order processing efficiency, accuracy, and scalability, enabling businesses to process email orders with minimal manual effort and greater precision.

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 provides an asset information acquisition method and device, a server, a controller and a medium, and relates to the technical field of servers, and the method comprises the steps: transmitting a command frame in a predetermined protocol format to a switch supporting a management endpoint function through a side link; wherein the command frame is used for indicating a lightweight proxy service module solidified in switch firmware to execute the following operations: analyzing the command frame, and directly accessing a configuration space of downstream target peripheral component interconnection high-speed equipment according to an analysis result to obtain original asset information, converting the original asset information into asset information conforming to a predetermined protocol format, packaging the asset information in the predetermined protocol format in a response frame, and returning the response frame to the baseboard management controller; and receiving a response frame returned by the lightweight proxy service module, wherein the response frame comprises the asset information in the predetermined protocol format. According to the method and the device, the asset information is independently obtained based on the substrate management controller, and the dependence on a BIOS (Basic Input / Output System) and burning is avoided.