2364results about "File/folder operations" patented technology

The invention relates to the technical field of intelligent processing of document information, discloses a method and a system for extracting RAG type data items and checking consistency for engineering technology documents, and solves the problem that an existing scheme is difficult to consider high-accuracy extraction, cross-document consistency, strong traceability and structured landing in engineering technology document data processing. The scheme comprises the following steps of: performing layout analysis and necessary OCR (Optical Character Recognition) processing on a received document, and dividing the document into multiple levels of text blocks; carrying out vectorization processing on the multi-level text blocks by adopting an embedding model subjected to two-stage fine adjustment, establishing a vector index and recalling candidate fragments to form a candidate fragment set; a cross encoder with efficient fine tuning of parameters is adopted to screen out high-correlation fragments; performing standardization processing by extracting a target variable to form a structured record; consistency checking is conducted on the target variables, and finally structured records and checking results are bound with minimum evidence fragments and corresponding position information to be exported through a format list.

The invention provides a code retrieval method and device and related equipment, and relates to the technical field of retrieval. The method comprises the following steps: segmenting each source code file to obtain a plurality of code blocks of each source code file; determining description information of each code block, and determining an association relationship between any two code blocks; generating a multi-layer code knowledge graph based on the description information of each code block and the incidence relation between any two code blocks; obtaining query information of a user, and determining a first code block based on the query information; determining a second code block related to the first code block in the multi-layer code knowledge graph; and generating a retrieval result by using the first code block and the second code block. Through the technical means, the problem of low code retrieval accuracy in related technologies is solved.

The invention relates to the technical field of electric digital data processing, and provides a secondary development code cross-product transplantation method and device, computer equipment and a medium. The method comprises the steps of loading a source project, screening a to-be-transplanted source code file, identifying an original API type, determining a mapping relation between the original API type and a target API type, and generating an adaptation layer code framework according to the mapping relation; copying the to-be-transplanted source code file into the target project; on the premise of keeping the project hierarchical structure of the source project, replacing the calling node of the original API type with the calling node of the adapter type, and replacing the namespace reference with the corresponding namespace in the target project to obtain a migrated source code file; and obtaining a secondary development project of the target project based on the second product API according to the adaptation layer code framework and the migrated source code file. According to the method and the device, the transplantation efficiency and accuracy of the transplantation of the cross-product secondary development codes are improved.

The invention provides a data weaving platform-oriented self-service data preparation method, which comprises the following steps of: accessing original data and associated structured metadata of a target data source into a data weaving platform to generate standardized accessed original data and associated structured metadata; based on a semantic model of the data weaving platform, performing classified semantic annotation on the associated structured metadata, and positioning a transfer node of the associated structured metadata to generate a data blood relationship record; performing bidirectional quality verification on the data consanguinity record according to semantics and path continuity, and matching with a federated governance rule of a data weaving platform to generate a metadata governance list; and generating a unified metadata directory based on the metadata governance list, so that a user of the data knitting platform can obtain key segments containing complete data consanguinity records. According to the method, the problem of insufficient accuracy and efficiency in self-service data preparation can be effectively relieved, and the efficient preparation requirement of a data weaving platform for multi-source data is met.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems, the creation, development, maintenance, and use of a set of custom objects (and core objects) for use in a wide range of activities, including sales activities, marketing activities, service activities, content development activities, and others, as well as improved methods and systems for sales, marketing and services that make use of such entity resolution systems and methods as well as custom objects.

The invention discloses an AI-based archive digitization full-process management and control method, which comprises the following steps: acquiring archive image data and text data, constructing an original archive data set, and generating an initial directory set; constructing an archive directory template set, executing template matching and structure adaptation, and generating an initial structure recognition result; setting a classification rule of directory deviation and structural contradiction, constructing a deviation rule base, executing rule scanning and node comparison, and generating a deviation contradiction label sequence; constructing an evolution state vector, inputting the evolution state vector into an improved GMN model, and generating a structure repair state vector through a structure guiding unit, a deviation sensing unit, a path fusion unit and a node evolution unit in sequence; and executing result updating and conflict rearrangement, completing standard template alignment and semantic coverage verification, and generating a final structure recognition result. According to the method, the structural integrity, the semantic consistency and the automatic repair capability of directory recognition are improved, and the method has relatively high adaptability and intelligent level.

The invention relates to the technical field of OA examination and approval, in particular to a multi-modal file intelligent examination and approval method and system based on a large language model, and the method comprises the steps: configuring exclusive examination and approval templates for different examination and approval roles, and generating a role exclusive intelligent examination model; the method comprises the following steps: receiving a to-be-approved multi-modal file, analyzing file content, and outputting structured JSON (JavaScript Object Notation) data; inputting the structured JSON data and a configured approval template into a corresponding intelligent review model, performing step-by-step reasoning through a thinking chain prompt strategy, and outputting a structured review intermediate result; encoding the review intermediate result into a semantic vector, and retrieving Top-K similar historical approval cases from a knowledge base module based on a vector database to generate a reference suggestion set; fusing the review intermediate result with the reference suggestion set to generate a review result; based on the review result and the feedback of the approver, the standardized approval opinions are generated, and the accuracy and consistency of review are improved.

The invention is suitable for the technical field of file management, and provides a file analysis method and system and a vehicle, the file analysis method and system are applied to a file analysis system, the file analysis system runs at a browser end, and the file analysis system comprises the steps that binary header information of a to-be-analyzed file is analyzed according to the byte position, obtained in advance, of the binary header information in the to-be-analyzed file, and the binary header information of the to-be-analyzed file is obtained; binary index position information of the to-be-analyzed file is obtained; according to the binary index position information, reading and analyzing binary index data of the to-be-analyzed file to obtain index data, determining a target data block meeting a preset requirement according to basic information of each data block, and reading the target data block; and analyzing the data in the read target data block to obtain formatted target data. According to the invention, the problem that the cost of cloud data storage and data analysis is increased due to the fact that a large amount of file data is analyzed and stored at the cloud in the prior art can be solved.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine-learning models to classify content items and automatically organize the content items within a file structure according to their content item classifications. For instance, a content item classification system generates one or more content item classification models to determine classifications for content items and / or folders. In some instances, the classification system detects when new content items are added to a smart folder, determines destination folders to which the content items belong based on classifying the content items, and automatically moves the content items accordingly. In various instances, the classification system generates and utilizes a classification model to organize content items into dynamically-generated folders. In example implementations, the classification system generates and utilizes a classification model to automatically organize existing content items into existing folders.

The invention relates to a digital archive intelligent processing method, a storage medium and a system, which are suitable for multi-source heterogeneous archive management scenes such as colleges and universities. The method comprises the following steps of: classifying structured and unstructured data such as paper archive scanning pieces and database views, and extracting metadata and entity information by adopting a scanning and OCR (Optical Character Recognition) technology; a complex table and document content are analyzed through a model, semantic analysis (entity recognition, relation extraction and event abstract) is achieved in combination with a language model of a Transform architecture, and a structured report containing a data abstract, an entity relation graph and abnormal annotations is generated. The system is internally provided with a parameter template automatic generation module, supports cross-page content continuous restoration and sensitive data encryption desensitization, and realizes safe sharing through an API interface. The method solves the problems of low efficiency, difficulty in multi-source data fusion and the like of traditional archive processing, improves the automation level and data value mining capability of archive management, and is suitable for intelligent upgrading of complex archive scenes.

The invention discloses an invalid code automatic elimination method and device, a medium and a product, and the method comprises the steps: carrying out compiling analysis processing on each program file in a to-be-processed target program item, generating a syntax tree model, and testing the compiled program file to obtain a program test result; unused variables in all the variables are identified through a syntax tree model, and uncovered code lines are positioned in combination with a test result; analyzing logic judgment conditions of uncovered code lines based on the syntax tree structure, and judging the code lines which cannot be triggered as unreachable codes; unused variables and unreachable codes in the program files are removed, new program items are obtained, and when the new program items are correctly compiled and executed, the new program items are used for replacing the target program items. Program redundancy is reduced, and execution efficiency is improved.

The invention provides a simulation test key factor screening-oriented method and system and a computer program product. The method comprises the following steps: generating a structured configuration file; constructing a supervised learning data set based on the structured configuration file; based on the supervised learning data set, training a machine learning classification model to obtain a current key factor set; and repeating the steps, judging whether the current key factor set is converged or not, and if the current key factor set is converged, stopping simulation and outputting the current key factor set of the last round as a final key factor. According to the technical scheme of the invention, a high-dimensional, nonlinear and high-coupling complex system can be automatically processed; key factors are objectively recognized through machine learning, a small-batch iteration verification mechanism is adopted, and the screening accuracy and efficiency are improved while the number of times of simulation is remarkably reduced.

The embodiment of the invention provides a large language model retrieval enhancement generation-oriented file processing method and device, and the method comprises the steps: carrying out the information extraction and semantic information enhancement of a file according to different file types, and constructing a meta-information structure of the file in combination with an enterprise business scene; dividing the document content into a plurality of structured blocks based on the meta-information structure, and labeling the title and context information of each block; when the file is uploaded, according to the parent directory material quantity and content change of the directory where the file is located, performing dirty marking on the directory; when a data request is received, whether a dirty mark exists in a related directory or not is judged, if yes, the directory is requested to be locked, a summary is extracted from files extracted from bottom to top through a large language model, and the dirty mark is cleared after the summary is cached.

The invention belongs to the technical field of nuclear power station file management, and particularly relates to an intelligent nuclear power station file classification and retrieval system based on artificial intelligence. The file acquisition module is responsible for uniformly acquiring and accessing multi-modal files in the nuclear power station; the preprocessing and natural language processing module is used for carrying out deep processing and semantic analysis on the collected multi-modal document; the dynamic classification module is used for carrying out multi-dimensional automatic classification on the multi-modal document based on a deep learning model and a nuclear power industry knowledge graph; the dynamic knowledge updating module is used for continuously monitoring new documents and user feedback and keeping adaptability to industry changes; the intelligent retrieval module is used for providing a query function for a user through semantic vectorization and a large-scale rapid retrieval technology; and the intelligent recommendation module is used for providing targeted document recommendation for the user through association analysis and collaborative filtering. According to the method, the problems of low classification efficiency, insufficient retrieval accuracy, weak dynamic adaptive capacity and limited multi-modal data processing capacity are solved.

The invention relates to the technical field of information security, discloses a realization method of an electronic signature of a customs business scene and a seal management system, and aims to solve the problems of trust centralization, easy data tampering, difficult traceability, poor business adaptation and insufficient interoperability of an existing electronic signature. According to the method and the system, a distributed account book technology is introduced, decentralized creation and registration, signature generation and verification, life cycle management and on-chain recording of auditing and tracing of the electronic seal are realized, a dynamic and configurable business scene strategy engine is constructed, a customs business process is flexibly adapted, and high safety, high efficiency and high adaptability are ensured. According to the method, a decentralized trust basis is established, the tamper-proofing capability and efficiency are improved, full-chain auditing traceability and cross-mechanism interoperation are realized, and data security is guaranteed.

The invention relates to a simulation result compression method and system based on semantic segmentation, equipment and a medium. The method comprises the following steps: performing feature extraction on a simulation result file to obtain semantic features; generating a segmentation point sequence according to the features by using a semantic segmentation model, and segmenting the file into a plurality of semantic blocks; extracting a compressibility feature vector for each block, and dynamically distributing an optimal compression strategy for the block through a prediction model; compressing each block by using the distributed strategy to generate a compressed data block; and finally, constructing a block sensing index based on the block type and the used strategy, and integrating the index and the data block to generate a compressed file. By adopting the method, the defects of limited compression ratio and incapability of supporting rapid random access caused by lack of semantic understanding of a general compression algorithm can be overcome, and by understanding the internal logic structure of the file and applying differential compression, the rapid retrieval and analysis capability of specific data is kept while the high compression ratio is realized.

The invention provides a log data reading method and device, equipment, a medium and a program product, and relates to the field of big data. Obtaining a mapping relationship between a plurality of timeline identifiers in a database and corresponding start log serial numbers; the timeline identifier is an identifier generated when the main database and the standby database are switched, whether the log data cross different timeline identifiers or not is judged according to the mapping relation and the starting log serial number and the ending log serial number of the log data, and under the condition that the log data cross different timeline identifiers, the log data cross different timeline identifiers. Reconstructing a log reading process according to a start log serial number of a new timeline identifier, wherein the new timeline identifier is different from the plurality of timeline identifiers; according to the method, automatic reconstruction of the log reading process after main and standby switching is achieved, the problems of low efficiency and poor real-time performance caused by manual operation are avoided, and continuity and consistency of data synchronization of the source end and the target end are guaranteed.

The invention belongs to the technical field of geographic information technology and remote sensing image processing and service, and discloses a slice-free image service system and method based on dynamic projection and real-time mosaic, which abandons the traditional pre-slicing mode, directly provides online service based on original image data, and improves the service efficiency. The problem of redundant storage caused by pre-generation and storage of massive tiles is fundamentally eliminated, and storage space is saved by up to 90%. Meanwhile, when the original data is updated, the system does not need to carry out a time-consuming re-slicing process, real-time updating and publishing of services can be realized, and the core pain points of long data updating period and high delay in the traditional technology are thoroughly solved. Through the integrated dynamic projection engine and the real-time mosaic module, the on-demand service request of the client for any coordinate system, any spatial range and any resolution can be responded.

The invention discloses a confidential evaluation compliance document automatic generation system and method based on strategic data management and control and full-link verification, and aims at solving the problems that traditional confidential evaluation document generation is low in efficiency, insufficient in safety protection, poor in expansibility and the like. According to the method, hard coding logic is replaced by a strategy engine center, a scene-template-strategy association mechanism is constructed, and full-process automatic generation of secret evaluation documents is achieved through scene configuration, intelligent template matching, parameter analysis, multi-dimensional data cleaning and desensitization, national secret standard automatic signing and full-process log management and control. The generation efficiency is remarkably improved, a sensitive data'identification-processing-protection 'safety closed loop is formed, the tamper-proof and auditing requirements of secret evaluation are met, a newly-added scene can be quickly accessed through strategy configuration, and the expansibility and reusability are excellent.

The invention relates to the technical field of electric power construction management, in particular to a full-chain-number intelligent construction collaborative management method and system based on electric power production. The method comprises the following steps: constructing a construction actual measurement parameter reverse mapping path, and reversely synchronizing a construction actual measurement data set to a design platform; structuring the change information in the debugging event log into measuring point mapping change data, and constructing a debugging change information reverse synchronization path based on a point construction loop three-way binding structure; constructing a dynamic transformer area operation portrait, introducing a transformer area deviation attribution identification model to compare the dynamic transformer area operation portrait with the static archive data to generate a transformer area operation deviation matrix, and dynamically adjusting a reactive power compensation control strategy and a load prediction model parameter; and performing unified archiving on the construction actual measurement data set, the measurement point mapping change data and the dynamic court operation portrait in real time. According to the invention, the reverse closed-loop collaborative management method for the whole life cycle of power production and construction is realized.

The invention discloses a batch file intelligent processing method and system in office development. The method comprises the steps of receiving and verifying parameters including a source directory, a target directory, a processing range and the like; traversing the directory based on the related path and the processing range, generating a structure, and collecting information to establish a file index; positioning the changed file by means of a file index, carrying out multi-dimensional difference comparison and recording a result; detecting codes and row separators in parallel for files in the file index and a target file provided by a user, generating a repair strategy and executing format repair; analyzing the natural language instruction based on the replacement rule to generate an executable rule set, and executing batch processing operation on the processed files; and summarizing various results to generate and store an output report. According to the method, intelligent batch processing of the files is realized, and the file processing efficiency and accuracy in office development are improved.

The invention discloses a QAR data processing method, system and device based on HDF5 and a medium, and relates to the technical field of data processing. An HDF5 file is generated by obtaining QAR data; dynamically analyzing the HDF5 file according to a preset event script to obtain configuration data and corresponding QAR parameter data; according to the configuration data, storing the QAR parameter data to obtain a plurality of JSON (JavaScript Object Notation) files, and forming a JSON database; and according to a query demand, reading the JSON file corresponding to the query demand in parallel from the JSON database to obtain a query result. By adopting the embodiment of the invention, the QAR data stream is analyzed in real time by analyzing the HDF5 file, a key event can be quickly identified and triggered in the analysis process, fault prediction, monitoring and elimination can be effectively carried out, and the QAR data monitoring efficiency and effect are improved.

The embodiment of the invention provides a video processor, a video processing method, video processing equipment, a storage medium and a program product. In the scheme, after the display layer receives the special effect style configuration, the algorithm engine layer calls the matched physical mathematical model according to the target special effect style and the basic video, outputs the high-fidelity special effect description file, and improves the special effect parameter accuracy; the rendering adaptation layer dynamically selects an optimal rendering engine according to the resources of all the rendering engines, and the time consumption of single-example rendering is shortened; two-layer hierarchical decoupling is adopted, so that description file generation and rendering execution are parallel, batch description files can be shared by multiple preview positions after being prepared at one time, rendering resources are only input when real preview requirements are met, and idling is avoided; the display layer, the algorithm engine layer, the rendering adaptation layer and the rendering layer are sequentially relayed to form a compact link of quasi-generation-fast rendering-playback, so that waiting and repeated export links of a user in a subsequent video editing stage are remarkably reduced, and the video editing efficiency is integrally improved.

The invention discloses an RAG knowledge base construction method and device and a medium, and the method comprises the steps: carrying out the analysis of the format, structure and semantic features of input data through a multi-level priority judgment logic, and automatically recognizing the specific data type. And calling a corresponding adaptive segmentation strategy for processing according to the identified data type, and generating data slices with semantic coherence. And asynchronously calling the large language model to generate a keyword set for each data slice, and uniformly storing the data slices, the keyword sets and associated multi-modal resource links by adopting a mixed storage mode to construct an enhanced RAG knowledge base. In the retrieval stage, query keywords are generated for user query according to the same logic, and related results are accurately retrieved from the knowledge base through a keyword matching mechanism. According to the method, the semantic segmentation problem is effectively avoided through intelligent segmentation with adaptive types, multi-modal data access is supported, and unified management and efficient retrieval of heterogeneous resources are realized.

The invention relates to the technical field of archive management systems, and particularly discloses an AI technology-fused archive digital efficient processing system, which comprises an intelligent acquisition preprocessing module, an AI deep identification analysis module, an intelligent classification archiving module, an AI retrieval optimization module and a security encryption module, automatic collection and unified processing of multiple types of archives are achieved through the intelligent collection and preprocessing module, operations such as denoising, deviation correction and format standardization are completed with the help of an AI algorithm, dependence on manual operation is avoided, and the archive preprocessing period is greatly shortened; through deep integration of the AI technology and the archive management service, the efficiency, accuracy and safety problems in existing archive digital processing are comprehensively solved, the archive management cost is reduced, the archive utilization value is improved, and reliable technical support is provided for archive digital management in various fields.

The embodiment of the invention discloses a virtual file management method, system and device and a storage medium. According to the technical scheme provided by the embodiment of the invention, under the condition that the file request is received, the virtual path contained in the file request is extracted, the virtual path is created when the target file is generated, path classification is performed according to the module identifier of the associated target service module, and the target file is stored in the system path mapped by the virtual path. The system path is generated by mapping based on the virtual path and a pre-constructed mapping rule; mapping the virtual path into a corresponding system path based on a mapping rule; and accessing the target file based on the system path to execute a file operation corresponding to the file request. By means of the technical means, the situation that file directory structures of different service modules are disordered can be avoided, unified file management of the different service modules in the application is achieved, the file management efficiency of the different service modules is improved, the application service effect is improved, and therefore the user experience is improved.

A method for managing data includes: receiving a file analysis request from a user, in which the request includes merging criteria, a first data path to access a first file, a second data path to access a second file, and a third data path to access a third file; obtaining the first file using the first data path, the second file using the second data path, and the third file using the third data path; analyzing the merging criteria; inferring, based on a determination, that the second file is suitable to be merged with the first file and the third file is not suitable to be merged with the first file; merging, based on the merging criteria, the first file and the second file to generate an output file; and initiating, via a graphical user interface (GUI), displaying of the output file to the user.

The invention discloses a distributed file backup method for a sonar database system, which belongs to the technical field of sonar data processing and comprises the following steps: acquiring file data containing underwater acoustic signal data from the sonar database system; fragmenting the file data to generate data blocks and dynamically adjusting the sizes of the data blocks; generating a unique identifier for the data block based on the content hash value and the metadata; selecting distributed storage nodes based on availability, storage capacity, network delay and geographical distribution factors; the transmission data block uses an encryption protocol; updating the storage position and state of the backup metadata record; periodically verifying the integrity and availability of the backup data; executing a data recovery process to recover the original file data; the dynamically adjusted backup policy is based on real-time operation requirements and data importance levels. According to the method, through distributed storage and dynamic optimization, the backup efficiency, the data security and the system reliability are improved, and the method is suitable for sonar data management in an underwater detection system.

The invention relates to the field of time capsule interaction, and discloses a time capsule interaction method and system, and the method comprises the steps: carrying out the logic unit segmentation of a to-be-sealed content, and building an encryption baseline which continuously evolves along with a time factor; under the support of an encryption baseline, performing fragmentation processing on the evolved and encrypted content, and triggering copy reconstruction through a witness mechanism when a node failure is detected; on the basis of a content storage link, continuously executing periodic health check in a storage period, and generating a state index in combination with a node online rate, key evolution integrity and user interaction history; when the key has an unrecoverable risk in the state index, triggering a multi-role collaborative recovery mechanism, and requiring a user side to submit a standby identity certificate; and after missing key reconstruction is completed, when preset opening time arrives, decryption operation is executed based on the key set which is finally evolved and completed and the recovered fragments, and an opening response with an interaction attribute is generated. The method has the advantage of improving the trust of the user.

The invention provides a resume information extraction method and device, electronic equipment and a storage medium, and relates to the technical field of automatic information. The method comprises the steps of obtaining a to-be-processed resume file; analyzing the resume file through a pre-trained resume information extraction model to obtain a file format and content characteristics of the resume file; determining a target extraction tool of the resume file according to the file format and the content features; and performing information extraction on the resume file through the target extraction tool to obtain resume text content. The resume information extraction model only needs to extract the file format and the content feature of the resume file, since the file format and the content feature of the resume file are easier to identify, a large amount of data is not needed for model training, and different extraction tools can be utilized to perform information extraction on different types of resumes, so that the extraction efficiency is improved. And the accuracy of information extraction is improved.