1078results about "File metadata searching" patented technology

The invention discloses a water conservancy design archive retrieval system and method based on a local lightweight large model, and the method comprises the steps: S1, constructing a Python automatic preprocessing assembly line, extracting texts for PDF and Word multi-format archives, correcting metadata, and outputting standardized data; s2, constructing a full-text retrieval and semantic retrieval dual-mode cross-document retrieval service by relying on a Weavi ate local vector database and a lightweight text embedding model; s3, analyzing a user query intention through a local large model, synchronously triggering metadata accurate retrieval and content semantic retrieval, and generating a structured result; and S4, integrating the core module into a local area network Web platform, adopting Docker containerization deployment, and combining an RBAC permission model and JWT authentication to guarantee security. The system comprises a preprocessing module, a cross-document retrieval module, an intelligent agent module and a background management module, and collaboration is achieved through a standardized API. According to the method, the problem of archive fragmentation is solved, multi-mode retrieval breaks through keyword limitation, an intelligent agent reduces manual intervention, a localized architecture prevents secret-related leakage, background management adapts to an existing I T environment, and full-process intelligent archive service is provided for water conservancy design.

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.

A metadata access method, apparatus, and computer-readable storage medium for efficient metadata retrieval through cache management. The method receives metadata query requests including target index information from processes and performs matching operations on a global cache file containing records with index information and slot identifiers. Each cache description array corresponds to memory blocks caching metadata. Upon successful matching, the target cache description array is accessed using the target slot identifier. The data state of target metadata is determined from the cache description array, and target address information indicating the location of the target memory block in shared memory is obtained and returned to the requesting process, enabling efficient shared memory-based metadata access.

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 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 the technical field of message recovery, and discloses an AI-based iOS device message recovery method and system, and the method comprises the steps: connecting an iOS device, positioning a database file of a message application, and obtaining a database file path list; reading an equipment storage sector, creating a physical mirror image, and analyzing a free block position mark in an APFS container super block; binary classification identification is carried out through an AI data block classification model, an SQLite page type label and a page mapping relation are obtained, deleted messages of a recombined database and a device end are determined, differential comparison is carried out on all historical backup snapshot records of an iCloud account, and cloud end deleted messages are obtained; according to the method and the system, the reorganization success rate of the database and the extraction integrity of the deleted messages are improved, and a technical solution is provided for comprehensive, accurate and efficient recovery of the iOS device messages.

The invention provides a file positioning management method and system based on artificial intelligence, and relates to the technical field of artificial intelligence. According to the method, files are collected from multiple sources and subjected to standardization processing, an element set is generated in combination with multi-modal analysis of texts, images, audios, videos and tables, cross-modal alignment is achieved through a semantic representation model, hierarchical indexes of semantics, keywords and relations are constructed, and a unique traceability identifier is generated; in the query stage, intention recognition and joint retrieval are carried out, a result subjected to permission verification and traceability information labeling is output, online optimization and incremental reconstruction are executed based on user feedback, and comprehensiveness, accuracy, traceability and self-adaptive optimization of file positioning are achieved.

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 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.

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 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.

The invention discloses a distributed file management system and method, and belongs to the technical field of computer software, the system adopts a tree hierarchical structure to organize files, and the system comprises an application layer used for receiving file operation requests from a plurality of independent clients, and each request carries a unique application identifier; the file system layer comprises a configuration module, an operation module, a metadata management module, a day module, a timed task module and a gateway module, and the request is routed to a corresponding logic storage partition in the data layer according to an application identifier; the data layer comprises a database cluster and an object storage cluster, and performs persistent storage and management of logic isolation on metadata and file data according to application identifiers; and the infrastructure layer provides an extensible server and network resources. Based on a distributed architecture, load balancing and efficient access are realized through data storage partitioning, a metadata management and index technology and a client load balancing technology, and the expandability, fault tolerance and performance of the system are improved.

The invention provides a storage device, a storage method and a storage access method based on lake and warehouse integration. The storage device comprises a storage management unit, a unified metadata management unit and a federal query engine unit, the storage management unit is used for realizing hybrid storage and dynamic hierarchical storage; the unified metadata management unit is used for metadata atlas construction, concurrency control and GDPR compliance support; the federal query engine is used for intelligent routing decision, SQL dialect unification and intelligent push-down optimization; based on a lake and warehouse integrated storage device and an access technology thereof, unified management of structured and unstructured data is supported, the problem of data islands is avoided, and cross-engine data visibility is realized through unified metadata management; according to the lake and warehouse integrated storage device and the access method, technologies such as a dynamic hierarchical storage strategy, intelligent routing decision, intelligent push-down optimization and the like are fused, and the storage and access efficiency and the robustness of the system are greatly improved.

A method, computer program product, and system are provided for managing encrypted files. A file is received, wherein the file comprises file metadata. A large language model identifies keywords from the file, and generates keyword vector(s) from the identified keywords. The file is encrypted and indexed with the keyword vector(s) and the file metadata in a protected index.

The invention provides a general semiconductor test data full life cycle management system, and the system comprises a test source data access module which is used for uploading a source test file in a test machine to the system; the full test data analysis and standard model conversion module is used for converting the uploaded source test file into a test file in a standard data format and transmitting the test file to the multi-dimensional KPI atomic model operation and persistent storage module; the multi-dimensional KPI atomic model operation and persistence storage module is used for calculating a multi-dimensional KPI atomic result according to the data in the test file in the standard data format and storing the multi-dimensional KPI atomic result to a persistence layer database; and the unified service output module is used for receiving a user query request, performing aggregation calculation on the multi-dimensional KPI atomic result in the persistent layer database according to the user query request, and returning a KPI result meeting the user query request. The system can improve the utilization efficiency of semiconductor test data and reduce the operation cost.

In general, techniques for efficient data retrieval from a backup system are described. An example computing system includes one or more storage devices and processing circuitry having access to the one or more storage devices and configured to: process an input to generate a filter, wherein the input indicates a context for one or more queries; apply the filter to backup data to obtain filtered data from the backup data; generate an index of embeddings from the filtered data; process, based on the index of embeddings, a query to generate a response for the query; and output the response.

An AI based system and method for processing and querying files. A method of processing files for an artificial intelligence (AI) querying service includes: hierarchically parsing the files into a set of hierarchically connected data chunks; generating metadata for each of the hierarchically connected data chunks, wherein the metadata includes hierarchical information; processing the hierarchically connected data chunks and metadata with an embedding model to generate vector embeddings that include the hierarchical information; generating textual summaries from the hierarchically connected data chunks; and storing the vector embeddings, textual summaries, and hierarchically connected data chunks for the AI querying service.

The invention relates to the technical field of data acquisition and treatment, and discloses a multimodal compatible global real-time full-amount active data acquisition and treatment method, which comprises the following steps: acquiring data source connection information of a regional medical platform, identifying potential data sources in a region, and constructing a feature portrait; matching an acquisition strategy for each data source and generating an acquisition task configuration; data acquisition is carried out, data of different data forms are analyzed, and data formats are unified; performing data cleaning, standardization and quality verification; carrying out sensitive field identification, and carrying out desensitization and encryption processing on sensitive information; performing association key extraction and entity recognition disambiguation; performing multi-source data intelligent association integration; matching the classified storage strategy and carrying out persistence processing, recording a processing process and carrying out interface development; according to the method, data cleaning, standardization, quality verification and privacy desensitization are pre-embedded into an acquisition process through a streaming collaborative governance mechanism, so that integrated processing of acquisition and governance is realized.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

The embodiment of the invention discloses an application service recommendation method and device, equipment and a medium, and the method comprises the steps: generating a rule data file of each application service based on the application service information of each application service of a current platform, carrying out the preprocessing of the rule data file, and constructing a description file knowledge base; wherein the application service information comprises item description and an access interface address; constructing a recommendation agent based on a preset large model, receiving a user side input demand based on the preset large model, and decomposing the user side input demand into a plurality of subtasks; inputting the subtasks and the cue words corresponding to the subtasks into the preset large model, so as to distribute the subtasks to the corresponding recommended agents based on a preset protocol; and searching the description file knowledge base according to the corresponding recommendation agent to obtain a matched description file and an access interface address corresponding to the matched description file, and returning the matched description file and the access interface address to a user side to realize application recommendation.

One or more embodiments of the invention provide a file system, method and device applied to a modern browser. The file system comprises a storage layer and a service layer, and the storage layer comprises a running memory and a source private file system; the service layer comprises a joint file system, and the joint file system is obtained by combining a temporary file system instance and a persistent file system instance; wherein a first file directory which is realized by relying on a running memory is created under the temporary file system instance, a second file directory which is realized by relying on a source private file system is created under the persistent file system instance, and access paths of the first file directory and the second file directory are the same. The access priority of the persistent file system instance is higher than that of the temporary file system instance.

A data processing architecture controls data processing arbitration in a high performance computing system that includes one or more premises. Individual premises can include one or more server computers executing an instance of a local file system and including one or more temporary data storage devices. Individual instances of the local file system can access files stored in objects of a primary data store. Individual objects of the primary data store can be accessed using a common identifier indicating a storage location of the individual objects in the primary data store.

The invention discloses a rapid identification and grading early warning method for sensitive files of customs field mobile equipment, and relates to the technical field of electronic data forensics, and the method comprises the following specific steps: constructing a sensitive key feature library, collecting and analyzing mirror image data, fusing and judging sensitive information, and automatically generating a sensitive grading early warning and risk report. According to the method, sensitive information samples of customs law enforcement cases, supervision notification cases and compliance public data sources are collected, and accurate extraction of four modal features of images, texts, audios and videos is ensured by using a multi-modal sensitive feature extraction formula; in the preliminary screening stage, file feature vectors are compared in batches through a preliminary screening similarity calculation formula, and suspicious files are quickly marked; in the recognition stage, multi-dimensional matching is adopted for files of different formats, and recognition confidence coefficients of all modes are generated; finally, whether the to-be-detected file is a sensitive file or not is judged through a comprehensive confidence coefficient calculation formula, and the omission ratio is reduced.

The invention discloses a code engineering automatic compiling construction method without appointing source code file paths one by one, and belongs to the technical field of software engineering. According to the method, makefile files are created under a code project path, unified src and inc folders are created in each level of catalog of a project to store source files and header files respectively, all file paths are obtained through automatic search, compiling and linking automation is achieved through a mode rule, and automatic generation of a dependency relationship and project solution construction are supported. The invention further provides a compiling construction method of the multi-code project. According to the method, the problem that Makefile or IDE setting needs to be repeatedly modified when code files are added and deleted and paths are modified is solved; the defect that code source file retrieval paths, header file retrieval paths, header file paths depended by compiling of source files and required object file paths need to be manually specified one by one for compiling in the prior art is overcome.

The invention discloses a file pre-reading method and device, a medium and equipment, and the method comprises the steps: firstly obtaining a file type of a target file, and executing pre-reading processing through a pre-reading window only when the target file is a continuous file; and dynamically adjusting the size of the window in combination with the hit condition of the pre-reading content on the basis: increasing the window in hit to improve the sequential reading efficiency, and reducing the window in miss to reduce the invalid pre-reading proportion. Through the above self-adaptive adjustment mechanism based on hit feedback, the size of the pre-reading window can be flexibly optimized for different access modes, and excessive pre-reading caused by a fixed pre-reading window in a random access or access mode change scene is avoided, so that unnecessary memory occupation and input and output resource waste are reduced, and the stability of reading performance is kept.

Techniques are provided for directory snapshot and data management. Conventional snapshot functionality creates snapshots at a volume level. Volume level snapshots are inadequate for scale-out storage architectures because a single volume snapshot of a shared storage resource may not satisfy different data protection requirements of clients using the shared storage resource. The disclosed techniques are capable of creating snapshots at a directory level. The directory level snapshots are created and maintained using an inode identity map to track active inode numbers of directory files that have diverged. Snapshot generation numbers are used to determine whether a file is part of a directory for which snapshotting is enabled. A version map used to track versions of a file modified across different directory snapshots and an active file system. A delayed free metafile is used to determine whether file block numbers of a directory can be freed.

The application discloses a block data archiving method and device for a blockchain and a medium. The method comprises the following steps: determining a block start number and a block end number corresponding to to-be-archived block data, constructing a to-be-executed archiving application through a private key of a to-be-archived blockchain node corresponding to the to-be-archived block data; publishing the to-be-executed archiving application on a chain, auditing the to-be-executed archiving application by an archiving smart contract in the blockchain, and publishing an archiving audit result; in the case that the audit is passed, packaging the to-be-archived block data by the to-be-archived blockchain node to generate a to-be-archived block data file and uploading the to-be-archived block data file to a preset storage area; after receiving a message notification of successful uploading, constructing a successful archiving notification based on an archiving application transaction Hash corresponding to the to-be-executed archiving application and a storage address of the to-be-archived block data file contained in the message notification, and publishing the successful archiving notification. The application avoids the risk of data loss or leakage and ensures that the archiving behavior is traceable.

The invention discloses a medical document processing method and system based on a double-pipeline architecture, and relates to the technical field of document processing. According to the medical document processing method based on the double-assembly-line architecture, through a closed-loop process of document classification, preprocessing, double-assembly-line directional parallel processing and hierarchical vectorization storage, precise adaptation and efficient processing of multi-format and multi-type medical documents are achieved, the information loss rate and the key information truncation rate are greatly reduced, and the medical document processing efficiency is improved. According to the method, the document processing efficiency and the data standardization degree are improved, the warehousing success rate and the data traceability of the vector library are ensured, high-quality and structured data source support is provided for subsequent medical intelligent retrieval, clinical question and answer and retrieval enhancement generation system application, the knowledge base construction and maintenance cost is remarkably reduced, and the method is suitable for popularization and application. The problems that in existing medical document processing, medical semantics are not taken into consideration, so that key clinical information is easy to cut off, and a single processing flow cannot adapt to a structured guide and an unstructured case are solved.

The invention provides a multi-modal large-model long-sequence information compression retrieval method, and relates to the technical field of data processing, and the method comprises the following steps: receiving multi-modal long-sequence original data of a target patient; all modal data in the multi-modal long sequence original data are uniformly mapped to the same hidden space through a pre-trained multi-modal large model, and a unified semantic representation sequence of semantic association between modals is obtained; performing time sequence feature analysis on the unified semantic representation sequence, regarding feature points in the semantic representation as a spatial point set, determining boundary distribution by constructing convex hulls of feature clusters, identifying key feature clusters in the semantic representation, and determining a key time sequence interval based on a convex hull distribution mode of the key feature clusters. According to the method, the problems of weak cross-modal semantic association, easy loss of key time sequence information and low compression and retrieval efficiency in the existing multi-modal long sequence data retrieval are solved.

A domain-focused natural language question and answer system. The system includes one or more electronic processors. The one or more electronic processors are configured to create, from a plurality of files, a plurality of fine-tuning data examples, each respective fine-tuning data example of the plurality of fine-tuning data examples including a question, an answer, and a supporting citation. The one or more electronic processors are further configured to fine-tune a pre-trained foundational machine learning model using the plurality of fine-tuning data examples to generate a fine-tuned machine learning model, input a natural language question to the fine-tuned machine learning model, and retrieve, from the fine-tuned machine learning model, a natural language answer to the natural language question and an indication of one or more files, one or more relevant sections, or both that the natural language answer is based on.