22 results about "Document transformation" patented technology

The present disclosure relates to a cloud-based system designed to automate the packaging, validation, processing, and delivery of media content and its supporting items. The system processes video, audio, subtitles, artwork, and metadata according to predefined specifications, ensuring compliance with technical and qualitative requirements for various endpoints. The system performs validation, error correction, transcoding, file conversion, and packaging based on saved profiles or templates. By leveraging cloud-based workflows and optional human oversight, the system ensures efficient and accurate delivery of media content to any destination.

The embodiment of the application provides a CAD-based model file conversion method and device, electronic equipment and a storage medium, and belongs to the technical field of data conversion. The method comprises the following steps: receiving a first model file input by a user, and determining a first CAD software corresponding to the first model file; determining a deformation parameter corresponding to the first model file, and generating a corresponding parameter mapping table based on the deformation parameter; generating a deformation request based on the first model file, the first CAD software and the parameter mapping table, and outputting a second model file corresponding to a second CAD software based on the deformation request. The embodiment of the application can realize model data conversion and sharing between different CAD software, improve the accuracy and efficiency of model file conversion, and further improve the efficiency of part selection and reuse.

The application relates to the technical field of deep learning compilation, and provides a method, device, equipment and medium for converting an MLIR file into a PyTorch file. The method comprises the following steps: obtaining an MLIR file, extracting data information and operation information in the MLIR file; retaining original identifiers of the data information and converting data types of the data information into Tensor data types in a PyTorch file; constructing a dependency relationship between operations according to a front-back order relationship between the operations; converting operation types in the MLIR file into operation types in the PyTorch file according to a conversion relationship between the PyTorch file and the MLIR file; and forming the PyTorch file according to the converted data types, the dependency relationship between the operations and the converted operation types. The method can equivalently convert the MLIR file into the corresponding PyTorch file.

A method includes converting a plurality of files stored in a database that stores transactional data for a software application into a plurality of JavaScript object notation files, wherein the converting is performed as the plurality of files is loaded into the database, storing the plurality of JavaScript object notation files in a plurality of buckets, invoking a plurality of batch operations, wherein each batch operation of the plurality of batch operations reads a subset of the plurality of JavaScript object notation files from one bucket of the plurality of buckets with a defined frequency, reading the subset of the plurality of JavaScript object notation files into a tabular data structure, writing the tabular data structure into the one bucket in an open source, column-oriented data storage format, and reading the column-oriented data storage format into a query service that supports structured query language.

The present disclosure relates to a file conversion method, apparatus, and non-transitory computer readable medium. The file conversion method can include receiving a controller area network (CAN) database container (DBC) file of a first type. The method can also include generating a first data frame containing signal names, message names, and message identifiers as information from the CAN DBC file of the first type. The method can also include converting the message names and the message identifiers from the first data frame to a second data frame by regenerating the message names and the message identifiers according to a predetermined rule. The method can also include generating a CAN DBC file of a second type from the second data frame.

The application discloses an intelligent display voice-to-text method and system and a medium, and the method comprises the following steps: when an audio and video file is captured, the audio and video file is converted into text; each sentence of text is segmented according to a pre-agreed punctuation mark to obtain segmented sentence text information; a pre-established dictionary table is searched; if historical data corresponding to the segmented sentence text information is found in the dictionary table, a corresponding previously combined text paragraph is obtained from the dictionary table; the text paragraph is rendered; single characters in the rendered text paragraph content are processed according to sensitive words, forbidden words or search words; and the processed single characters are synchronized with the text paragraph on a page for display. Through the application, a user can quickly find out where a violation is located, and can also quickly jump to a corresponding progress for manual auditing to confirm whether a problem exists, thereby greatly reducing the workload of the user for compliance processing.

The application relates to the technical field of data processing, and discloses a file processing method, equipment, a storage medium and a program product. The file processing method comprises the following steps: an electronic device generates a first table file based on at least one identification information group (an ID identifier and a signal group name) in a DBC file. Moreover, preset editing content (for example, ASIL and E2EID) corresponding to each identification information group can be inserted into the first table file to obtain a second table file. Then, the electronic device extracts each row of text data of the DBC file to obtain a list database, and adds list data meeting a parameter rule to a first list dictionary database. Next, the corresponding preset editing content is filled into each identification information group in the first list dictionary database based on the second table file, so that a second list dictionary database is obtained. Finally, a target file is obtained based on the second list dictionary database. In this way, the efficiency of converting the DBC file into the target file can be improved, and the time cost of a user can be saved.

This paper describes a method, system, and computer storage medium for providing an advertising campaign management engine within an artificial intelligence system. Advertising campaign management refers to the process of planning, executing, monitoring, and optimizing advertising campaigns. Operationally, it first involves high-conversion design modeling and mining analysis of performance data and user preferences to identify design elements (such as image style and text layout) that enhance engagement. Next, design requirement generation transforms ad optimization profiles into structured prompts that guide the refinement of ad design. Finally, design fine-tuning utilizes advanced generative models to adjust ad elements (such as images and layout) based on generated requirements. The advertising campaign management engine supports an iterative process that enables automatic updates and optimization, allowing ads to be customized based on specific demographics. For example, it can create unique designs for young people or simplified layouts for older people. The refined ads are then deployed and continuously monitored for performance improvement.

This application discloses a file conversion method, apparatus, electronic device, and computer-readable storage medium, aiming to achieve a more efficient and accurate conversion of interface screenshots into editable design drafts. The method includes: acquiring a screenshot of the interface to be converted and its interface layout features; processing the screenshot using an interface element detection model to obtain each interface element and its element features in the screenshot; the element features include at least the type features, position features, and attribute features of the corresponding interface element; constructing each interface element as a design node based on its element features; matching the node attributes of each design node with the element features of the corresponding interface element; determining the relationships between each design node based on the interface layout features, and organizing all design nodes into multi-node hierarchical structured data based on these relationships; and importing the multi-node hierarchical structured data into a target design tool to generate an editable design draft corresponding to the screenshot of the interface to be converted.

This invention provides a WebAssembly model protection system for browser-based secure inference. The system, through the collaborative work of a model parsing and storage module, a model conversion and compilation module, a security enhancement module, and a front-end API generation module, converts model files from different machine learning training frameworks into WebAssembly model files that can run independently in the browser. During the conversion process, it integrates and encapsulates model structure information, model weight information, and model computation logic, and enhances their security, achieving comprehensive security protection for the front-end model. This invention, by integrating model format conversion, WebAssembly compilation, and customized obfuscation technologies, constructs a highly secure and practical Web model protection system, significantly improving the resistance to reverse engineering of Web machine learning models, effectively preventing model theft and tampering risks, and is suitable for the secure deployment of AI applications on various browsers.

Embodiments receive a portable document format (PDF) from a user computing device; convert the PDF to a JPEG file by utilizing an artificial intelligence (AI) image segmentation model; convert the JPEG file to a text file by utilizing an AI vision workflow model; parse and classify the text file using a first large language model (LLM); determine a textual study guide using a second LLM; generate a question and answer exam based on the textual study guide using a third LLM; and generate a multiple choice question (MCQ) exam based on the question and answer exam using a plurality of LLMs.

This disclosure relates to a policy loading method, apparatus, electronic device, storage medium, and program product. The method includes: in response to a policy file change event, determining a changed policy file, the policy file including a policy logic description; converting the policy file into a bytecode array conforming to a preset syntax specification, the preset syntax specification allowing the bytecode array to be converted into a policy class object at runtime; converting the bytecode array into a policy class object; in response to a policy execution instruction, determining a target policy class object from the policy class objects based on the policy execution instruction, creating a target policy instance based on the target policy class object, and executing the target policy instance. Specifically, when a new policy file is uploaded, it can be loaded in real-time at runtime, thus eliminating the dependency chain of encoding, compilation, packaging, release, and restart, shortening the loading cycle of the new policy file, improving the loading response speed of the new policy file, and meeting the needs of business scenarios with high real-time requirements.

The application relates to the technical field of file identification, in particular to a port business confirmation letter identification method, system, device and medium, which comprises the following steps: obtaining a business confirmation letter file; converting the business confirmation letter file into business confirmation letter image data; performing primary extraction on the business confirmation letter image data to obtain primary extraction information; analyzing the primary extraction information to determine whether the seal part content and the table part content are successfully identified; if both are successfully identified, taking the primary extraction information as a business confirmation letter identification result; if there is a part of the content that is not successfully identified, performing secondary processing on the part to obtain a business confirmation letter identification result; and encapsulating the business confirmation letter identification result into JSON structured data. Through the primary extraction and secondary processing cooperative mechanism, the dynamic identification result credibility evaluation and the structured data encapsulation technology, the application realizes the full-element accurate extraction of the guarantee letter key information, the automatic closed-loop analysis and the efficient interaction of the business system.

The application provides a processing method and device of a briefing file, an electronic device and a storage medium. The method comprises the following steps: obtaining an original briefing file to be processed and a target file type, wherein the target file type is a file type that can be supported in a target application; processing the original briefing file according to the target file type, obtaining a target briefing file with the target file type, and editing the target briefing file in the target application. Thus, the original briefing file is converted into the target briefing file with the target file type that can be supported in the target application, so that the target briefing file can be edited in the target application.

The present application relates to the technical field of data conversion, and provides a data processing method and apparatus. In the method, an AUTOSAR configuration tool can acquire a configuration file and a configuration rule file corresponding to the configuration file, and obtain an ARXML file on the basis of the configuration file and the configuration rule file. The configuration rule file is used for indicating a rule corresponding to the conversion of the configuration file to the ARXML file. When a configuration file is newly added, an ARXML file corresponding to the configuration file can be obtained by simply newly adding a corresponding configuration rule file, without updating the AUTOSAR configuration tool. The development and maintenance workload of the AUTOSAR configuration tool is reduced, and the configuration file processing efficiency is improved.

The application discloses a scanning version file conversion method and system integrated secret-related detection and belongs to the technical field of digital management, and aims to solve the technical problem of how to realize batch processing of scanning version archives, improve file conversion speed and meet the time requirement of the archive management department on large-scale cabinet type conversion. The method comprises the following steps: traversing all relevant scanning version files in the source file path and the subdirectory specified by a user, loading configured secret-related keywords and matching rules; calling C# to perform file disassembly and recognizing the files through OCR recognition technology to label the files with corresponding secret-related level tags; generating OFD files based on the picture layout data and the extracted text data of the disassembled files through memory stream technology; importing the OFD files and corresponding metadata into an archive library and storing key analysis data into the database of the archive management system; and manually checking file processing records, secret-related inspection results and OFD files.

This specification provides an electronic invoice processing method and apparatus. One electronic invoice processing method includes: firstly, acquiring invoice issuance data and invoice file format during electronic invoice processing; reading invoice rendering resources corresponding to the invoice type identifier in the invoice issuance data; performing format adaptation calculations on the invoice issuance data according to invoice format rules and the type format rules corresponding to the invoice type to obtain invoice format data; further, assembling and converting invoice data based on the invoice format data, invoice rendering resources, and invoice template data matching the invoice type to obtain HTML data of the target invoice; and finally, calling the file conversion interface corresponding to the invoice file format in the invoice rendering component to process the HTML data to obtain the invoice file, thereby obtaining the invoice file corresponding to the invoice file format.

This paper presents a method for constructing a regulatory and standard knowledge base based on a large language model. The method involves the field of natural language processing and includes: acquiring multiple regulatory and standard documents and converting them into text data; performing semantic segmentation of the text data using a large language model based on prompt words, generating results including: text blocks, block indexes, hierarchical path information, and parent node indexes; each text block includes at least: the directories at each level of the full-level directory structure, and optionally includes: the main text content corresponding to each level of the directory; extracting entity relationships and keywords based on the results generated from the semantic segmentation using a large language model, and generating hierarchical summaries; constructing a document index; and storing the text blocks, block indexes, hierarchical path information, parent node indexes, and document indexes into the knowledge base according to a predefined knowledge storage structure; the knowledge storage structure includes at least an index area, an entry text area, and a case area. The regulatory and standard knowledge base constructed in this application can improve retrieval efficiency and accuracy.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment. 20 26 20 53 12 06 J ul 2 02 6 2 0 2 6 2 0 5 3 1 2 0 6 J u l 2 0 2 6

The application discloses an aero-engine software tracing and checking method and system, realizes full-process automatic tracing from requirement definition to final verification, shows the tracing relationship in an intuitive mode, improves the efficiency and quality of software development, and provides support for aero-engine software development and maintenance. The technical scheme is as follows: a link relationship is established: a plurality of requirement files and traced files are linked through different tools or methods, and the link relationship between high and low layer requirements and data is verified; after each source file with the link relationship is acquired, the source file is converted into an intermediate file through a converter, the intermediate file contains format information, the tracing relationship in the intermediate file is extracted by analyzing a keyword, and a coverage range is acquired; based on the tracing rule checking, the wrong tracing relationship is located and modified; and a visual view is formed according to the tracing relationship.

The application relates to the field of artificial intelligence and discloses a multi-modal document retrieval method, system, terminal and storage medium based on multi-vector embedding, the method comprising the following steps: carrying out image conversion processing on a PDF file according to a preset definition to obtain a document image; carrying out embedding vector generation processing on the document image to obtain a plurality of document image feature vectors, and carrying out embedding vector generation processing on a query sentence set to obtain a plurality of query feature vectors; constructing a similarity score matrix according to the plurality of document image feature vectors and the plurality of query feature vectors, and carrying out retrieval processing on the document image according to the similarity score matrix to obtain a retrieval result; and generating a query result according to a query intention and the retrieval result. The PDF file is converted into a document image, embedding vectors are respectively generated according to the document image and the query sentence set for retrieval, different formats of return results are generated according to user intentions, and the accuracy of document retrieval is improved.