3180results about "File system administration" patented technology

The invention relates to the technical field of archive management, in particular to an archive full life cycle management system and method based on cloud computing. The method specifically comprises an intelligent classification module based on a format adaptation degree function and semantic density analysis, a five-stage life cycle management module, and an authority scheduling module fusing RBAC / ABAC authority control and block chain auditing, and based on a matrix decomposition archiving static coding mechanism, document security storage and analysis are realized through an orthogonal matrix and pseudo-inverse operation, and the file security is realized. The data security in a long-term archiving scene is improved; cloud storage resources are dynamically optimized according to the document life cycle state and the access frequency, and the storage cost is reduced in combination with a cold and hot layering strategy; and an AI algorithm is introduced, the archive retention value is automatically evaluated according to laws and regulations and semantic analysis, and a compliant destruction decision is realized. According to the method, through multi-model fusion metadata extraction, dynamic strategy binding and automatic state transition, the whole-process management efficiency and safety are remarkably improved.

The invention relates to the technical field of archive management, and discloses an AI and encrypted storage-based archive management method, which comprises the following steps of: preprocessing original archive information by using a natural language processing algorithm to generate structured archive data, and performing multi-level classification through a dynamic classification tree model. Data are encrypted by adopting a hybrid encryption technology, and encrypted archive data blocks are constructed and stored in a distributed database. And performing parallel retrieval by using a multi-modal retrieval model, performing decryption according to user permission and scenes based on a dynamic decryption strategy, and finally transmitting data through a secure channel. In addition, the system also has the functions of file data updating and version control, log access and anomaly detection, cross-mechanism file sharing and the like. The efficiency, safety and intelligent level of archive management are improved, and the problems existing in traditional archive management are effectively solved.

The invention discloses a knowledge base generation and retrieval method based on the RAG technology and an intelligent question answering system, and belongs to the technical field of natural language processing, and the knowledge base generation and retrieval method based on the RAG technology and the intelligent question answering system based on the RAG technology have the beneficial effects that the accuracy and the real-time performance of information processing are improved through efficient combination of retrieval and generation. High-dimensional vector representation is generated through text slicing and vectorization, a vocabulary index is constructed, and hierarchical retrieval and keyword matching are achieved; meanwhile, a question generation and question-question retrieval method is utilized, a result is optimized and generated in combination with a large language model (LLM), the reasoning ability of the large model is further improved through chain reasoning (COT) and a cue word optimization module, and it is ensured that the generated answer has high accuracy and logicality; the method can be widely applied to the fields of intelligent question answering, knowledge base construction, real-time information retrieval and the like.

The invention discloses a fusion method for automatic coprocessing of multi-source heterogeneous data, which comprises the following steps of: analyzing the format and semanteme of the multi-source heterogeneous data to obtain metadata features of each data source, the metadata features comprising data types, coding modes and semantic tags, and generating a standardized metadata description set; according to the metadata description set, a pre-established protocol template library is adopted, an applicable template is matched, an initial unified exchange protocol is generated, and the initial unified exchange protocol comprises a format conversion rule and a semantic mapping relation; and if the format conversion rule of the initial unified exchange protocol cannot adapt to the metadata features of the newly added data source, dynamically updating the protocol template through a machine learning algorithm to obtain an exchange protocol adaptive to the new data source.

The invention provides an AI agent memory management method and system based on cold and hot stratification, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining and preprocessing the historical information of an AI agent, and carrying out the vectorization storage of the historical information; calculating a score based on the access frequency and the semantic association; constructing a dual-threshold triggering mechanism to realize data cold and hot layered migration; establishing index mapping and dynamically monitoring data popularity for returning; and a storage water level dynamic adjustment migration strategy is monitored in real time. According to the invention, the problem of low memory management efficiency of the AI agent is solved, efficient access of memory content is realized, and the storage cost is reduced.

The invention provides an electronic certificate management and supply chain quality tracing method and system based on a block chain, and belongs to the technical field of information. According to the method, encryption storage and tamper-proof protection are carried out on the electronic certificate information through the distributed account book of the block chain and the Hash algorithm, and verification, approval and data updating operations are automatically executed based on the intelligent contract. Fine-grained authority management and abnormal access detection of all parties of the supply chain are realized through a user access control module; and through a tracing query module, performing multi-condition combination query on the electronic certificate information stored in the block chain, and generating a quality tracing report meeting supervision requirements. According to the method, through tamper-proofing, distributed storage and intelligent contracts of the block chain, trusted storage, automatic verification and full-chain quality tracing of the electronic certification are realized, data security and supply chain transparency are improved, trust cost is reduced, and supervision and tracing efficiency is improved.

The invention relates to the field of data backup, in particular to an intelligent data backup method and system based on an AI large model. The method comprises the following steps: acquiring an enterprise global data list, performing intelligent data structure deconstruction and dynamic attribute mapping modeling, and constructing a holographic data semantic perception model; performing real-time transient risk mutation detection on the holographic data semantic perception model, and constructing an intelligent backup triggering mechanism; carrying out storage resource demand prediction based on an intelligent backup trigger mechanism, carrying out multi-storage cloud environment resource dynamic scheduling, and constructing an elastic backup storage resource pool; carrying out incremental backup analysis and self-adaptive compression coding to obtain an incremental backup coding packet; and performing dynamic backup sequence adjustment and intelligent incremental backup decision on the incremental backup coding packet based on the elastic backup storage resource pool, and constructing an intelligent incremental backup execution engine. According to the method, the reliability, the accuracy and the traceability of a backup result are improved through self-adaptive intelligent incremental backup.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

The invention relates to an engineering document index consistency proofreading method and system based on a multi-modal large model, and the method comprises the steps: Q1. OCR detection and recognition: carrying out the optical character recognition and format analysis of a source document, converting an uploaded PDF document into a processable text message in a Markdown format, and carrying out the format discrimination of a table, a formula and a plain text; and Q2, table and formula processing: adopting a hierarchical processing strategy, intelligently selecting an optimal processing mode according to the complexity of the table, and converting table information into a descriptive long text through a language large model and cue words. According to the method, accurate, reliable and efficient document index checking service can be provided for a user, the quality and efficiency of professional document processing are remarkably improved, the efficiency and quality of knowledge graph construction are remarkably improved, a knowledge verification system capable of being evolved continuously is established, and the method is suitable for popularization and application. And a reliable technical support is provided for knowledge management and professional decision-making in a complex field.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

The invention discloses a human resource archive filing management system, and relates to the technical field of data management, the system comprises an acquisition module, a processing module and a management module, the acquisition module acquires original archive data of employees, transmits the data to the processing module, classifies the original archive data according to a preset first rule, and stores the classified data to the management module; the first archive data is obtained, controlled and managed, a calling permission and a distribution strategy are generated, the first archive data is recognized through a preset second rule, second archive data is generated, corresponding processing is conducted according to the processing priority, a processing log is reserved, third archive data are obtained and transmitted to the management module, and the management module is used for managing the first archive data. A distributed cloud storage cluster and a local storage node are constructed, an overall storage architecture and a retrieval path of third archive data are optimized, archive management is refined through three-dimensional classification, data integrity is guaranteed through field-level verification and automatic completion, scene-based dynamic authority control safety is achieved, compliance risks are intelligently cleared and avoided, and efficiency is improved through mixed storage. And active management of archive management is promoted.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

The invention provides a conference system, an intelligent agent and a conference processing method, and the system comprises an edge device which is used for carrying out the preliminary screening and feature extraction of a conference link file, and determining a first feature; the cloud server is used for analyzing the first feature after receiving the first feature sent by the edge device, and determining a conference link and conference starting time; the clock and network state monitoring module is used for evaluating the quality of a network environment where the intelligent agent is located within a first preset time before the conference starting time after receiving the conference link and the conference starting time sent by the cloud server, and selecting an optimal network access strategy to access the conference; the knowledge graph construction module is used for constructing a first knowledge graph according to the conference data; the conference recording and analyzing module is used for performing real-time translation according to the source language and the target language of the spokesman during the conference; and analyzing the conference content by adopting the optimized pre-trained large model and a multi-modal fusion algorithm to generate a conference summary document.

Techniques are described for efficient replication and maintaining snapshot data consistency during file storage replication between file systems in different cloud infrastructure regions. In certain embodiments, provenance IDs are used to efficiently identify a starting point (e.g., a base snapshot) for a cross-region replication process, conserve cloud resources while reducing network and IO traffic.

Techniques are described for efficient replication and maintaining snapshot data consistency during file storage replication between file systems in different cloud infrastructure regions. In certain embodiments, snapshot creation and deletion requests that occur during cross-region replications may be temporarily withheld until appropriate times to execute such requests safely, depending on the timing relationship between such requests and cross-region replication cycles.

The invention relates to the technical field of data processing, and discloses a real-time data stream processing method and device, electronic equipment and a storage medium. The method comprises the following steps: distributing a received to-be-processed data stream to a first distributed node through a preset load balancer; fragmenting the received distribution data stream at the first distributed node according to a preset fragmentation rule, then writing the fragmented data stream into a message queue, and performing parallel processing on fragmented data in the message queue through multiple threads; storing the intermediate state data in the fragmented data processing process, generating snapshot data according to the fragmented data, and synchronizing the snapshot data to the distributed storage system; acquiring load data of the first distributed node, and dynamically updating a data flow distribution strategy of the load balancer according to the load data through the resource use prediction model; and writing a processing result of the to-be-processed data stream into persistent storage through an asynchronous batch mechanism, and returning the processing result through a preset real-time communication protocol. The method improves the data stream processing efficiency and stability.

The invention discloses an intelligent archive content evaluation system based on deep learning, which relates to the technical field of deep learning, and comprises the steps of inputting a standardized feature vector into a deep learning model, calculating a time sequence waveform factor and a semantic kurtosis factor in combination with a rule matching reference, and generating an evaluation confidence coefficient matrix; the cosine similarity and the Spearman correlation coefficient are included, and the comparison index threshold triggers abnormal marking and grading early warning. According to the method, a multi-model fusion deep learning evaluation model is constructed and comprises a semantic understanding model, a risk evaluation model and a value classification model, split attributes are dynamically optimized in combination with an evaluation rule decision tree, file contents can be comprehensively evaluated from multiple dimensions of semantic understanding, risk evaluation, value classification and the like, and the evaluation efficiency is improved. And an accurate comprehensive evaluation result and a rule matching reference are generated, so that the comprehensiveness and scientificity of file content evaluation are improved.

The invention discloses a BIM model-based digital twinning and panoramic camera mapping method and system, and relates to the technical field of BIM and digital twinning, and the system is mainly composed of a data acquisition module, a data preprocessing module, a feature extraction and analysis module, a coordinate conversion and matching module, a digital twinning model module and a display module. Real-time and efficient integration of the video data and the BIM model is realized, and then the digital twin model capable of accurately reflecting the current state of the building is constructed. The model is of great significance to comprehensive monitoring and management of the building environment, and the intelligent level and the operation and maintenance efficiency of the building are remarkably improved.

The invention belongs to the field of data storage, and discloses a frequency access data storage migration method and device for big data, and the method comprises the steps: obtaining a data access log, carrying out the preprocessing of the data access log, and obtaining a time window statistical matrix; carrying out timeliness attenuation weighting calculation on a plurality of data access times in the time window statistical matrix to obtain a weighted access frequency vector; obtaining a multi-dimensional feature matrix based on the weighted access frequency vector; clustering the feature vector of each time window slice in the multi-dimensional feature matrix through a Gaussian mixture model to obtain a clustering tag vector; inputting the clustering label vector into an access frequency prediction model to obtain an access frequency prediction value of the data in a future preset time step; the migration decision matrix is determined based on the access frequency predicted value and the data storage cost parameter, data migration is carried out based on the migration decision matrix, the data migration complexity can be reduced, and the access speed and the storage cost are balanced.

The invention belongs to archives, and particularly relates to an investment and financing project archive evidence intelligent management platform based on big data, which comprises the following steps: step 1, a system uploads and preprocesses archives through an upload and storage module, and converts project files in different formats into structured data; 2, a data processing and intelligent analysis module automatically extracts key information and performs archive classification, data matching and compliance review by using natural language processing and a machine learning algorithm on the basis of data of the uploading and storage module; 3, the system carries out automatic examination based on the compliance model, an evidence chain meeting legal requirements is generated, real-time risk assessment is carried out, and when potential risks are recognized, the system triggers early warning and provides suggestions; step 4, in combination with risk early warning and legal examination data, a system workflow and task scheduling module dynamically schedules a workflow according to a task priority and a dependency relationship; and 5, providing decision support by the system through a user interface, and helping a manager to make a precise decision.

The invention discloses a file storage management method and system based on computer system resource use, and particularly relates to the technical field of file storage management. Triggering a data migration operation through a preset storage space upper limit, distinguishing file access characteristics in high and low load scenes, dynamically evaluating the accuracy of file priority judgment by an AI algorithm, judging whether priority judgment is reasonable or not by calculating an access frequency abnormal index and calling frequency fluctuation, and dividing judgment results into an accurate class and an inaccurate class; for an accurate judgment result, a management strategy of high and low priority files is further optimized; and for the inaccurate judgment result, the weight of the file access frequency and the weight of the recovery calling frequency are fed back to the AI model, the judgment capability of the AI model is continuously optimized, the risk of file priority misjudgment is effectively reduced, and the accuracy of a data migration decision and the stability of system storage resources are improved.

The invention discloses a regional refined sea wave coupling numerical forecasting method based on a non-static mode, and aims to improve forecasting accuracy. The method comprises the following steps: firstly, constructing a regional refined sea wave coupling numerical forecasting system consisting of a data collection subsystem, a preprocessing subsystem, a data assimilation subsystem, a coupling mode calculation subsystem and a post-processing subsystem; the data collection subsystem obtains related data of atmosphere, ocean and sea waves; the preprocessing subsystem generates atmosphere, ocean and sea wave mode grid files and interpolates atmosphere, ocean and sea wave forecast fields to obtain preprocessed data, namely an atmosphere initial field, an atmosphere boundary field, an atmosphere forced field, an ocean initial field, an ocean boundary field and a sea wave boundary field. The data assimilation subsystem assimilates the preprocessed data to obtain assimilated data; and the coupling mode calculation subsystem performs integration on assimilated data to obtain forecast fields of atmosphere, ocean and sea waves. And the post-processing subsystem generates a forecast product according to each forecast field. The method is small in forecasting error and high in forecasting accuracy.

The invention relates to the technical field of data management, in particular to a visual data processing system applied to traditional Chinese medicine pediatrics. The system comprises the following modules: a data acquisition module used for acquiring a pediatric physiological time sequence data set; carrying out physiological event anchor point identification on the pediatric physiological time sequence data set to obtain a physiological event anchor point set; the time calibration module is used for performing noise suppression on the pediatric physiological time sequence data set according to the physiological event anchor point set to obtain a noise-suppressed physiological time sequence data set; performing time calibration on the noise suppression physiological time sequence data set to obtain a time correction physiological data set; the feature extraction module is used for extracting a tongue picture image set from the time correction physiological data set; and generating a tongue picture feature vector set based on the tongue picture image set. According to the method, the problem of dynamic association analysis caused by multi-dimensional sign data isomerism in traditional Chinese medicine pediatric clinical data processing can be effectively solved.

Embodiments are directed to workload allocation for file system maintenance. A file system that includes storage nodes and snapshots may be provided such that each snapshot may be associated with a plurality of data blocks. If snapshots are deleted further actions may be performed, including: determining the dead blocks associated with the deleted snapshots such that each dead block may be a data block that may be unassociated with undeleted snapshots; adding the plurality of dead blocks to dead trees located on the storage nodes; determining an urgency score based on a workload model and file system metrics; determining delete tasks based on the urgency score; determining a portion of the storage nodes based on a number of delete tasks; and executing the delete tasks on the portion storage nodes to delete the dead blocks to return storage capacity to the file system.

The invention discloses an artificial intelligence-based bidding document automatic writing method and system, and the method comprises the steps: recognizing a project bidding document through a bidding document understanding module, extracting the requirements of the bidding document from the project bidding document, automatically recognizing materials according to the extracted requirements of the bidding document, and continuously updating a material database; according to the method, related materials are automatically obtained from a material database, a first to-be-processed bidding file is automatically generated according to the requirements of the recognized bidding file, a second to-be-processed bidding file is generated after the first to-be-processed bidding file is automatically compared, optimized and modified by a learning module, and a final version of bidding file is generated after manual confirmation by a system using unit. The method automatically identifies the bid invitation file requirements, continuously updates the material database, automatically matches the bid invitation file requirements, automatically generates the bid invitation file, and is convenient to use, short in time consumption, efficient and accurate.

The invention relates to the technical field of distributed system transaction management, and discloses an inventory consistency management method and device based on distributed transactions, and the method comprises the following steps: pre-occupying an inventory, and recording the state information of the inventory to a Redis hash structure; after the inventory is pre-occupied successfully, generating a pre-deducted snapshot, generating a compensation identifier, and writing the pre-deducted snapshot and the compensation identifier into a MySQL transaction log together; verifying the uniqueness of the compensation identifier, and submitting the current database transaction after the uniqueness of the compensation identifier is confirmed; when the submission of the current database transaction fails, executing a compensation operation on the current database transaction; and after the compensation operation is executed, performing data consistency verification on the MySQL transaction log and the Redis hash structure. According to the method and the system, the consistency of inventory management during distributed transaction processing is highly guaranteed.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data migration method, device, equipment and medium based on task offload, which comprises the following steps: scanning a source end directory hierarchy and a target end directory hierarchy, and generating source end file metadata and target end file metadata; files are classified into source-end unique files, target-end unique files and two-end shared files based on file paths, and the files are transmitted to a comparison processing module; generating a source end newly-added migration task, a difference coverage migration task and a target end deletion migration task; and transmitting the migration task to a migration processing module and executing the migration task to generate a migration result. According to the method, source-end unique files, difference files and target-end redundant files are processed in a classified mode, full-amount migration is disassembled into incremental tasks to be executed in a split mode, and the invalid data transmission amount is reduced; a difference coverage task is generated based on double comparison of metadata and content, repeated coverage of homonymous files is avoided, and redundant data is automatically cleaned.

The invention relates to the field of databases, and discloses an archive-based data management method and system, which can complete aggregation management of most business data in a single archive, reduce high relational operation overhead caused by multi-table association, and significantly improve flexibility, security and consistency of data management. According to the method, firstly, multiple objects are abstracted from a business scene or a real concept, a main object is selected, other objects related to the main object are aggregated in the same archive model, and the archive model comprises attributes for structured, sequential, log and unstructured data references or pointers. The file model is described through predefined metadata, and a logic structure, integrity constraint, a physical storage position, a storage period, a file model validity period, file attributes, and multi-version management, transaction control and authority control strategies oriented to addition, modification, deletion and check operations are set in the metadata.

Systems and methods for dynamically evaluating metadata consistency and data reliability in a data management system are disclosed herein. The system may retrieve first metadata and second metadata. The system may retrieve a metadata ruleset. Based on the metadata ruleset, the system may generate a first metadata consistency metric indicating a first measure of consistency. The system may determine to process each record of the first metadata as a batch. The system may generate a second metadata consistency metric indicating a second measure of consistency. The system may determine to process each record of the second metadata independently.

The invention provides a presentation file quality detection method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the field of document quality detection. According to the specific implementation scheme, a to-be-detected presentation file is obtained; wherein the to-be-detected presentation file comprises a plurality of pages of slides; converting each page of slide in the to-be-detected PowerPoint into structured data in a preset format; wherein the structured data represents elements contained in the slide and the distribution condition of the elements; determining a quality score of the to-be-detected PowerPoint according to the structured data corresponding to each page of slide; wherein the quality score represents the quality of the to-be-detected presentation file. And in combination with the element layout condition of each page of slides, the quality detection precision of the PowerPoint is improved.