1277 results about "Information transformation" patented technology

The invention discloses a building engineering automatic compliance examination method based on AI and BIM, and the method comprises the steps: obtaining a to-be-examined standard text, carrying out the natural language processing, and generating a semantic information group; by adopting a semantic mapping rule, mapping the semantic information group subjected to the information conversion algorithm and entity attributes in the IFC ontology structure, and by utilizing a logic rule generator, converting a mapped target NLP deep learning rule knowledge model into a logic rule; obtaining a to-be-examined BIM model, constructing a plurality of specific IDM views, extracting entity attributes corresponding to a specific field from the to-be-examined BIM model, mapping the entity attributes in each specific IDM view and the entity attributes in the IFC ontology structure, and converting the mapped target IFC engineering feature semantic model into a logic fact by using a preset conversion tool; and performing automatic compliance review on the logic rules and the logic facts by utilizing a rule engine through a rule reasoning algorithm and an ontology semantic reasoning algorithm to obtain a rule check report.

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 relates to the technical field of industrial automation, and discloses a method for detecting abnormal operation of industrial control equipment based on industrial control protocol analysis, which comprises the following steps of: 1, acquiring operation data of the industrial control equipment through at least one industrial control protocol which is a Modbus protocol, an OPC UA protocol or a PROFIBUS protocol, the operation data comprises sensor data, register data and equipment state data of the equipment; and 2, analyzing the collected data packet by using a protocol analyzer, extracting key information related to the equipment operation state, the key information comprising parameters such as equipment working frequency, load, vibration, temperature and pressure, and converting the key information into a uniform data format. By collecting, analyzing and analyzing the operation data of the industrial control equipment in real time, abnormal conditions in operation of the equipment can be found in time, spreading of equipment faults is avoided, and stable operation of the equipment is guaranteed.

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 method and device for automatically converting a cross-format document into a Markdown document and a form enhancement method and system. The Markdown document conversion method comprises the following steps: firstly, obtaining a document image; mining hidden structure information from the document image, wherein the hidden structure information comprises target elements and hierarchical relationships among the target elements; performing semantic content analysis on the document image based on the structure information to obtain a semantic content analysis result; extracting key information in the document image according to an analysis result; the key information is converted into a Markdown format, preliminary formatting is carried out in a form or list mode, and a preliminary Markdown form is obtained; and finally, optimizing the preliminary Markdown form to form a target Markdown form, so that the cross-format document is automatically converted into the Markdown. According to the method, a complex nested structure and a form with irregular layout in the document can be effectively identified and converted, and the integrity and readability of form information when the form is converted into the Markdown format are ensured.

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 discloses a collaborative design method and system based on a CAD platform, and particularly relates to the technical field of data processing. Data of a plurality of heterogeneous CAD software are collected and subjected to format analysis, geometric accuracy loss is analyzed and evaluated through curved surface deviation, parameter changes in the collaborative design process are monitored through an event monitoring mechanism and a difference updating technology, parameterized constraint retention rates among different CAD platforms are calculated, and parameter information conversion integrity is evaluated; constructing a data conversion quality evaluation model, comprehensively analyzing geometric accuracy and parameter retention conditions, and dynamically adjusting a CAD data conversion strategy by adopting an adaptive optimization algorithm for low-quality conversion data to improve cross-platform data integrity; according to the method, the data intercommunity, the design consistency and the conversion quality of CAD collaborative design are effectively improved, and an efficient and intelligent solution is provided for multi-software collaborative design and manufacturing.

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 the technical field of natural language processing, in particular to a knowledge base-based self-adaptive hybrid retrieval enhanced question and answer method and device.The method comprises the following steps of: extracting entities in an initial text to form a triple; converting the structured information of the triple into text retrieval information and vector retrieval information, and constructing a basic data source; presetting a query question level, judging the complexity of a to-be-queried question, and if the to-be-queried question is a first question, directly obtaining an answer by utilizing semantic matching; if the to-be-queried question is a second question, extracting a keyword of the to-be-queried question, and obtaining structured data of entities and relationships in the basic data source based on the keyword to obtain a retrieval result; and reordering based on a retrieval result to generate a question answer. The retrieval path is adaptively selected according to the depth of the problem in the retrieval process, so that the efficiency of simple query is improved, and deeper graph structure support is provided in complex query.

A computing system receives information indicative of interactions between a user and previously recommended items. The computing system transforms the information into a feature embeddings list. The computing system applies a heterogeneous self-attention model to the feature embeddings list. The heterogeneous self-attention model learns individual query, key, and value projection matrices for each feature embedding. The computing system generates a unique transformation matrix for each pair of feature embeddings. The computing system concatenates the individual query, key, and value projection matrices into a single concatenated matrix and generates a full projection matrix by at least applying a linear transformation to the single concatenated matrix. The computing system applies a heterogeneous interaction transformer model to the feature embeddings list to generate a weighted feature embeddings list including weighted task embeddings. The computing system generates a set of recommended items based on applying a projection function to the weighted task embeddings.

The invention relates to the technical field of big data management and data analysis, and discloses a visual data platform full-link data flow traceability method, system and device and a medium, and the method comprises the steps: monitoring a job scheduling process submission event, analyzing the input and output configuration information of each job node, converting the information into a data flow model, and storing the data flow model in a traceability database; static analysis is conducted on node scripts and codes, and analysis results are stored in a traceability database; generating a unique identifier for each data record, and recording related information in a data circulation process; and writing the data flow relationship into a graph database Neo4j through a Kafka asynchronous message, and performing data traceability query by a user through a visual interface. The method has the beneficial effects that the data quality and safety are improved, and the limitation and complexity of a mainstream open source tool in the aspect of a data blood relationship analysis function are solved.

The invention discloses a BIM (Building Information Modeling) full information analysis and conversion method based on a light database, which comprises the following steps: S1, preparing BIM data, traversing a design model in a source file, and establishing a linear design model structure tree; s2, BIM data analysis: traversing elements in all design models in the linear design model structure tree, and analyzing a full information data structure, including geometry, attribute and material information, of the elements; s3, BIM data conversion is carried out, the element information obtained through analysis is classified and converted into database objects capable of being recognized by a light database, and the database objects adopt a full-information data structure and are written into a user-defined database file. According to the method, full information conversion of BIM data can be achieved, it is guaranteed that element geometry, attribute and material information in the model are not lost, high data conversion and storage efficiency and element-level updating synchronization are achieved, the effects of data seamless circulation and shared application are achieved, and the data delivery and application requirements for various scenes in the infrastructure field are met.

The present application relates to the field of autonomous driving, and in particular relates to an occupancy grid prediction method, an occupancy grid prediction apparatus for implementing the method, a computer storage medium for implementing the method, and a smart device having the occupancy grid prediction apparatus. The method comprises: acquiring a pure visual image of the surroundings of a vehicle body; inputting the pure visual image into an occupancy grid prediction model; and using the occupancy grid prediction model to determine an occupancy result of an object in the pure visual image as a model output. The model output is an occupancy result in a cylindrical form, and the occupancy grid prediction model is constructed on the basis of a training dataset comprising sample images and truth value information of the sample images. The truth value information is directly generated from point cloud data or converted from occupancy information in a voxel form generated on the basis of the point cloud data.

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.

The invention discloses a downlink resource scheduling method and device for a 5G differentiated scene and a storage medium. The method comprises the following steps: acquiring information, wherein the information comprises time slot network state information of each time slot; converting the information into historical state track information; the historical state track information serves as input vectors to be input into a DQN neural network and a TD3 neural network respectively, and core parameters are output; respectively training a DQN neural network and a TD3 neural network according to the historical state trajectory information and the core parameters to obtain a trained DQN neural network and a trained TD3 neural network; the time slot network state information of the current time slot serves as a current input vector to be input into the trained DQN neural network and the trained TD3 neural network, and a current core parameter is output; calculating the priority of each user for each resource block based on a priority formula of a heuristic algorithm according to the current core parameter; and performing resource scheduling on the resource blocks based on a greedy strategy according to the priority. According to the method, the defects of a traditional priority-based scheduling algorithm in a complex network environment are overcome.

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 embodiment of the invention discloses a document generation method and device, electronic equipment, a storage medium and a program, and relates to the technical field of financial science and technology. The method comprises the following steps: acquiring key process element information of each key process element in a target development process; constructing a multi-tuple model of a development process document according to the key process element information; converting the information of the key process elements included in the multi-tuple model into a knowledge graph; and converting the knowledge graph into a development process document of the target development process. According to the technical scheme provided by the embodiment of the invention, the efficiency, flexibility and accuracy of development process document generation can be improved, and the readability and maintainability of the development process document 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.

Provided in the present description are a DDL statement conversion method for incremental data migration, and a related device. The method comprises: in response to triggering an incremental data migration task between a source end database and a target end database, acquiring a source end DDL statement which has been executed in the source end database and conforms to a syntactic rule of the source end database; analyzing the source end DDL statement to obtain operating information contained in the source end DDL statement in respect of the source end database and, on the basis of a predefined data format, converting the operating information into a corresponding structural body; and converting the structural body into a target end DDL statement conforming to a syntactic rule of the target end database, and executing the target end DDL statement in the target end database.

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 provides an intelligent government affair question-answering method and an intelligent government affair question-answering device for enhancing a large model by combining speech recognition with a database, and relates to the technical field of intelligent government affair question-answering, comprising the following steps: S1, a speech recognition system is responsible for accurately converting a user speech instruction into a written text as a primary link of information conversion; and S2, the user intention analysis is used for accurately converting a user voice instruction into a written text, and then the text input is input into the large language model. According to the scheme, the convenience of user interaction is finally improved through the voice recognition technology, the user is allowed to rapidly interact with the system through the natural language, manual input is not needed, the information acquisition speed is increased, services are easier to access, and secondly, the natural language processing capacity of a large model is improved, and the user experience is improved. Therefore, the system can understand complex query intentions and provide accurate and humanized answers, and the naturalness and accuracy of query are enhanced.

The invention discloses a tool recommendation method and device and electronic equipment. The method comprises the following steps: receiving tool use demand information input by a target object; converting the tool use demand information into a demand semantic vector; a first candidate tool set corresponding to the demand semantic vector is determined from a first hash space, a second candidate tool set corresponding to the demand semantic vector is determined from a second hash space, the first hash space is a hash space corresponding to tool information of all tool sets, and the second hash space is a hash space corresponding to tool information of all tool sets; the second hash space is a hash space corresponding to the tool calling requirement; determining a target candidate tool set according to the first candidate tool set and the second candidate tool set; and recommending the target candidate tool set to the target object. The technical problem that a huge tool set affects accurate prediction of a large language model on tool calling requirements in the prior art is solved.

The invention relates to a work order generation method and device based on mail information, equipment and a storage medium, and the method comprises the steps: analyzing a to-be-processed mail, obtaining the text information and sender information of the to-be-processed mail, obtaining the voice description information inputted by a customer service user for the text information, converting the voice description information into target text information, and sending the target text information to a server; wherein the target text information is associated with semantics of the body information, extracting a semantic text of the to-be-processed mail based on the body information and the target text information, extracting semantic keywords corresponding to the semantic text and a question type represented by the semantic text, determining a work order template based on the sender information and the question type, and sending the work order template to the to-be-processed mail. And filling the semantic keyword and the semantic text into a work order template to generate a target work order. The work order can be accurately generated in combination with the text information of the mail and the target text information.

The invention discloses an information desensitization method and system, electronic equipment and a storage medium, and the method comprises the steps: firstly receiving a first query request of a user, recognizing each piece of target information in the query request according to a recognition rule, converting each piece of target information into a set identifier, and obtaining a second query request containing the set identifier; and calling an API key corresponding to the LLM model, and sending the second query request and the API key to a server providing the LLM model service. In this way, secret-related and / or privacy information in the query request of the user can be effectively filtered and hidden, and leakage of the secret-related and / or privacy information in the query request is avoided.

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.