104 results about "Technical documentation" patented technology

The invention discloses a method for analyzing a matching degree between a demand and an output result based on text semantics. The method comprises the following steps: step 1, labeling a data set; step 2, technical document preprocessing; 3, training and predicting a single-parameter model; 4, integrating prediction results of the multi-parameter model; the method has the beneficial effects thatthe method is simple; deep learning and the NLP technology are applied to the field of project association degree calculation of enterprise project management for the first time. Calculating an association matching degree between the two projects according to project requirements and result description; the associated project positioning difficulty is effectively reduced; meanwhile, the demand side can be helped to quickly and efficiently locate high-quality projects adapting to the demand of the demand side; time and resource investment for achievement screening and matching are greatly reduced, the association matching degree between projects is calculated by means of text data of existing project achievement technical documents and project declaration guidelines, and then large enterprises are assisted in screening high-quality projects with the high matching degree in the project bidding and tendering link.

Systems or techniques are provided for facilitating retrieval augmented generative question and answer boosting. In various embodiments, a system can access a plain text question regarding a scientific instrument. In various aspects, the system can generate, via a large language model that references a document-graph repository, a structured or unstructured answer for the plain text question. In various instances, the document-graph repository can comprise a plurality of document-graphs that respectively correspond to a plurality of technical documents. In various cases, for a first document-graph that corresponds to a first technical document, leaf nodes of the first document-graph can represent respective text blocks written in the first technical document, and non-leaf nodes of the first document-graph can respectively represent a document title, one or more section headings, and one or more scientific instrument identifiers written in the first technical document and beneath which the respective text blocks are nested.

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.

A computer-implemented system for automated document generation receives user input and processes it through artificial intelligence models to create professional documents. The system combines user-provided information with specialized knowledge databases containing domain-specific requirements and formatting standards to generate enhanced processing instructions. Trained machine learning models process these instructions to produce contextually appropriate content that addresses specific technical and legal requirements. The generated content is formatted using configurable templates to create completed documents that meet professional standards. The system provides adaptive user interfaces that adjust functionality based on user expertise levels, supports multiple operational modes including guided and automated generation, learns from example documents to improve output quality, and enables comprehensive workflow management through network-accessible services. Applications include patent applications, legal responses, technical documentation, and other specialized professional documents requiring domain expertise and regulatory compliance.

The invention discloses a long document knowledge base construction method based on directory perception and a program product, and belongs to the field of artificial intelligence and natural language processing. According to the scheme, an original long document is sequentially subjected to preprocessing, directory structure analysis, mixed blocking, double-tag generation, tag intelligent optimization, vectorization and meta-information mounting, and finally automatic construction and high-quality retrieval enhancement generation of a knowledge base are achieved. According to the method, the semantic integrity is guaranteed by fully utilizing the perceptual ability of the directory structure, the label quality and the retrieval efficiency are improved by combining a double-label system and intelligent optimization circulation, and the construction efficiency, the retrieval accuracy and the result traceability of the knowledge base are remarkably improved; the method is suitable for intelligent processing and application of long complex structure documents such as academic specialities, technical documents, policies and regulations and the like.

The invention discloses a research and development platform language intelligent analysis method based on multi-system fusion, and relates to the technical field of language intelligent analysis. According to the method, various language data in a multi-system fusion research and development platform are efficiently processed, cleaned and coded to generate a standardized data set by customizing a data adaptation interface, deep lexical and syntactic analysis and semantic role labeling are performed on the standardized data set, related features are extracted, a semantic mapping network is constructed, and semantic feature vectors are generated; cross-modal feature fusion is realized, deep meanings of language data are comprehensively captured, rich feature input is provided for intelligent analysis, a constructed intelligent analysis model can perform accurate intelligent analysis and intention recognition on natural language instructions and technical documents, and the intelligent analysis model can be used for performing intelligent analysis and intention recognition on the technical documents by means of compiling environment simulation, debugging information semantic optimization and the like. The model training effect is improved, and the analysis accuracy and the hardware compatibility are improved through hardware behavior simulation, real-time data flow analysis, user feedback and other modes.

The invention relates to the technical field of big language model dialogue system optimization, in particular to a big language model dynamic dialogue history compression method and system.The method comprises the steps that the maximum length of a context window matched with a target big language model, the maximum number of newly-generated lexical elements and the size of a safety buffer area are set, and then dialogue history is loaded; initial compression and verification are carried out through a keyword and TF-IDF mixed scoring system, multiple times of dynamic compression are carried out according to gradients if the conditions are not met, and finally, parameters are adjusted to adapt to the residual space when a model is called to generate response. The system comprises a dialogue history loading module, a parameter configuration module, a dynamic compression engine module and a large language model integration module. Through a multi-stage compression verification mechanism and a progressive multi-stage dynamic compression strategy, super-long texts such as engineering technology documents can be processed, service interruption is reduced, the compression efficiency is improved on the premise that key semantics are reserved, and multi-language dynamic compression is supported. The problems of system token overrun and service instability in the prior art are solved.

A method for technical issue resolution. The method includes: receiving, from a user, a text query concerning a technical issue; obtaining query-related context relevant to the text query; and processing, through a large language model (LLM), the text query and the query-related context to produce a multimodal query response used by the user to address the technical issue. More specifically, embodiments described herein utilize text topic and zero shot classification models to translate multimodal technical documentation (e.g., including text and images) into topic relevant metadata; and process queries, pertaining to technical issues, using a multimodal LLM provided with query-related text and image context derived from said topic relevant metadata.

The invention relates to the technical field of knowledge management, in particular to a construction technology knowledge management method and system based on a knowledge base and a large language model.The method comprises the steps that original construction technology documents are collected and preprocessed to obtain construction technology documents, then the construction technology documents are stored, and a knowledge base of the construction technology field is constructed; based on a natural language processing technology, identifying entities and semantic relationships among the entities from the construction technology document, and constructing a knowledge graph of the construction technology field; generating a construction technology question and answer model based on a pre-trained language model, a knowledge base and a knowledge graph; on the basis of a search engine, querying a construction technology document most related to query content input by a user from a knowledge base; and receiving query content input by a user through the interactive operation page, and displaying a query result or displaying a construction technology question and answer result. According to the invention, intelligent integration, dynamic updating and accurate service of knowledge can be realized.

Taxonomy driven multi-system networking and content delivery systems and methods are provided herein. An example systems includes a website authoring platform generating a taxonomy structure for a webpage, the taxonomy structure indicating assets to be included in the webpage a layout for the assets, a technical documentation authoring system for creating technical documents related to the assets, and a metadata binder providing the technical documentation authoring system with access to the taxonomy structure of the website authoring platform so that technical document authors are provided with the taxonomy structure to guide creation and structuring of the technical documents so that the technical documents comprise data that corresponds to the assets.

The invention discloses a programming method and system for industrial robot operation teaching based on a knowledge graph, and relates to the technical field of industrial automation and intelligent control. The method comprises the following steps: analyzing an industrial robot PDF technical document, extracting an instruction and an instruction parameter, and constructing a tree structure based on an identified title hierarchy; constructing a hierarchical knowledge graph based on the tree structure; generating an abstract syntax tree based on the instruction, the instruction parameter and the knowledge graph; filling node attributes of the abstract syntax tree into a preset control template, generating a reference RAPID code, importing the reference RAPID code into a robot controller, loading teaching environment parameters, and executing; and comparing execution results of the student self-compiled code and the reference code for students to observe difference comparison learning. The invention aims to break through a PDF technical document understanding threshold and accurately position errors in self-compiled codes of students through knowledge graph construction and reference code generation, so that the learning efficiency of the students is improved, and the teaching burden of teachers is relieved.

A method for generating technical documentation corresponding to source code is provided. In response to a repository selection received from a user terminal 110, the device 100 receives repository information related to the repository from a code management system 130 (S201 to S203). The device 100 then extracts multiple API code candidates and one or more root file candidates from the repository information (S204). The device 100 then requests a generative AI model (k) to determine paths for the multiple API codes and one or more root files using the extracted file candidates (S205) and receives the determined paths (S206). For each API code, the device 100 requests a generative AI model (l) to generate API documentation corresponding to the API code, and receives and stores the generated technical documentation (S207 to S209).

The invention provides an industrial product parameter extraction method based on domain knowledge learning, and the method comprises the steps: 1, collecting a plurality of technical documents of a preset industrial product field as knowledge sources, and constructing a structured domain knowledge model through a man-machine cooperation mode; 2, based on the domain knowledge model, generating a training data set with entity type labels, and training one or more deep learning extraction models by using the data set to enable the extraction models to learn parameter knowledge of the industrial product field; 3, receiving a new to-be-processed digital technology document, and processing the document by adopting the trained deep learning extraction model so as to identify and extract structured data corresponding to parameter entities in the domain knowledge model; and 4, storing the extracted structured data into a database, and selectively utilizing the data to carry out iterative updating and enhancement on the domain knowledge model.

The invention relates to an AI-based 3C product export compliance automatic detection method, which comprises the following steps: monitoring laws and regulations issuing platforms of 37 national supervision organizations at a frequency of not less than 30 minutes per time through a distributed crawler cluster deployed at a plurality of geographic nodes, and obtaining technical laws and regulations updating data of a target export country; a dynamic compliance mapping knowledge domain with a version tracing function is constructed, nodes comprise a standard term entity, a test method entity and an exemption condition entity, and edges comprise a logic dependence edge, a conflict edge and a reference edge. According to the AI-based 3C product export compliance automatic detection method, through collaborative optimization of a distributed crawler cluster and a hybrid neural network, single product detection is shortened to 3.4 minutes, vision-text-signal three-mode coupling analysis is constructed, the bottleneck of single-mode processing is broken through, the technical document analysis speed is increased by 18 times, real-time frame processing is achieved through video stream analysis, and the detection efficiency is improved. The 60fps video stream delay is less than 0.1 s, and the detection efficiency is remarkably improved.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and computing entities for displaying content found in technical documentation for an item via an IETM viewer. In accordance with one embodiment, a method is provided comprising: providing a window for display via the IETM viewer, the window displaying the content found in the technical documentation; receiving a focus of a first portion of the content received based at least in part on the user performing a first action; and in response, causing the first portion to be conveyed using a first enhancing format; and thereafter: receiving a focus of a second portion of the content received based at least in part on the user performing a second action; and in response: causing the first portion to no longer be conveyed using the first enhancing format; and causing the second portion to be conveyed using a second enhancing format.

The application relates to the technical field of distributed applications, and discloses a document synchronization method for code change, which comprises the following steps: in response to a code deployment request, monitoring code change through a change capturing engine and obtaining a unified change set; performing document paragraph positioning on an interface definition file according to the unified change set, constructing a change-paragraph mapping list and a document synchronization task; performing acceptance review on the document synchronization task based on acceptance rules to obtain a review result; and making a decision based on a blocking condition and the unified change set, the change-paragraph mapping list and the review result to determine whether to block code deployment and complete document synchronization. The method can realize accurate positioning of abstract code change to technical document paragraphs, form a unified and feasible evidence chain to jointly drive a document synchronization process and decision-making. The application further discloses a document synchronization device for code change and electronic equipment.

The techniques discussed herein enhance the operation of content generation and analysis systems. Namely, textual content applications such as technical documentation, creative writing, and content moderation. This is accomplished through generating a graphical representation of a body of text (e.g., a document). The graphical representation can comprise a plurality of nodes representing the words of the document and a plurality of lines that join the nodes representing a level of association between individual words. As such, the graphical representation can capture the semantic and syntactical structure of the associated document while omitting the original textual content. The graphical representation can be subsequently evaluated for complexity based on the density of nodes and lines. Accordingly, the disclosed system can assign a score to a document based on the evaluation of the graphical representation. In addition, various documents can be ranked based on such scores.

The application provides a technical document automatic generation method, system, device and storage medium, the method comprises the following steps: analyzing a demand document through a feishu intelligent slice, and extracting complete content; an intelligent agent actively inquires a user to obtain an interface name, an application ID and an interactive picture link, triggers corresponding MCP to obtain interface data and interactive documents, and performs integrity check; in combination with demand, interface and interactive content, the intelligent agent inquires technical stack information, and generates a standardized technical document by using a prompt word engineering. Then, a double check mechanism is started: the intelligent agent can automatically correct the error, and the user is asked to confirm the ambiguous demand until the document is correct; finally, the feishu document generation MCP is triggered, the demand, interface, interaction and final document are integrated into a Markdown format, and a link is pushed to an AI programming tool for generating code. The application can realize full-process automatic conversion from a demand document to a technical document in a Web webpage development scene, and provide a standardized technical basis for an AI programming tool.

The invention discloses a method and a system for automatically generating a technical document driven SDK (Software Development Kit) based on a large model, and belongs to the technical field of software development and artificial intelligence. The method comprises the following steps: intelligently cutting a technical document to generate a plurality of logically independent sub-document fragments; combining the sub-document fragments with a preset generation instruction template, and inputting the combined sub-document fragments and the preset generation instruction template into a large language model; receiving a structured code snippet which is returned by the large language model and corresponds to a project structure defined in the instruction template; integrating the code snippets to generate an initial SDK; and verifying the initial SDK and performing iterative optimization according to a result until a final SDK is generated. By combining the large language model and the standardized instruction template, full-automatic and intelligent generation from the technical document to the high-quality SDK is realized, a low-efficiency development mode depending on manpower is thoroughly changed, and development efficiency, code quality and normalization are remarkably improved.

A method for technical issue resolution. The method includes: receiving, from a user, a text query concerning a technical issue; obtaining query-related context relevant to the text query; and processing, through a large language model (LLM), the text query and the query-related context to produce a multimodal query response used by the user to address the technical issue. More specifically, embodiments described herein utilize text topic and zero shot classification models to translate multimodal technical documentation (e.g., including text and images) into topic relevant metadata; and process queries, pertaining to technical issues, using a multimodal LLM provided with query-related text and image context derived from said topic relevant metadata.

The invention discloses a real-time context sensing dynamic cue word generation method based on large model translation. The method comprises the steps of initialization, context sensing and core concept extraction, dynamic cue word generation, new concept recognition and list updating. According to the method, a traditional static translation process is converted into a dynamic process with memory and state maintenance capabilities, a global core concept list is constructed and dynamically maintained in real time, and dynamic cue words containing determined standard translations are automatically generated in the translation process; the global consistency of the translations on core concepts such as term named entities is remarkably improved, the problem that core concept translations are inconsistent in long document translation is fundamentally solved, and the method is suitable for professional fields such as technical documents, academic papers and commercial reports with extremely high term consistency requirements.

The embodiment of the invention provides a technical document processing method and a related device, the method is applied to a system controller, a knowledge query system supported by a production line technology comprises the system controller and a plurality of production line controllers, and the technical documents corresponding to the production line controllers are different. The method comprises the following steps: analyzing a plurality of technical documents according to text title coordinates to obtain analysis results corresponding to the plurality of technical documents; wherein the analysis result comprises a corresponding relation used for representing the text title and the local document content in the technical document; and issuing the analysis result to a corresponding production line controller, so that the production line controller responds to the production line knowledge query instruction based on the analysis result. The knowledge query efficiency can be improved.

The invention provides an equipment electronic manual system manufacturing platform, which belongs to the technical field of equipment electronic manual and comprises a data entry module, a data uploading module and a three-dimensional display module. The method has high adaptability and expandability in design. The system can support creation and maintenance of various types of electronic manuals, and simple operation guide and complex technical documents can be easily handled. In the face of diversified requirements of different industries and different user groups, the design of each functional module enables the system to be easy to carry out function expansion and customization. For example, along with the development of a three-dimensional technology, a three-dimensional model function module can be further upgraded to support more complex models and interaction modes; when a new image format appears, the image maintenance sub-module can be conveniently updated. The adaptability and the expandability enable the system to keep advancement and practicability for a long time, and the system has strong competitiveness in a continuously changing market environment.

The embodiment of the invention provides a product prototype interface generation method and device, electronic equipment and a storage medium, belongs to the technical field of artificial intelligence, and is suitable for the field of financial science and technology. The method comprises the steps of obtaining a product demand document of a target product; performing document analysis on the product demand document to obtain original document elements; performing structured conversion on the original document elements to obtain an initial document prompt template; performing logical reasoning on the initial document prompt template to obtain a product technical document; performing code conversion based on the product technical document to obtain a product prototype code; and performing page rendering based on the product prototype code to obtain a product prototype interface of the target product. According to the embodiment of the invention, the accuracy of product prototype interface generation can be improved.

The invention discloses an engineering FPGA automatic simulation test system and method based on an RAG enhanced large language model, and relates to the field of FPGA test and verification, and the system comprises a system input processing module which is used for carrying out the preprocessing of a received technical document and a to-be-tested piece source code, and carrying out the verification of the received technical document and the to-be-tested piece source code; the document analysis LLM enhancement module analyzes the preprocessed technical document based on a large language model; the code analysis LLM enhancement module analyzes the preprocessed source code of the to-be-tested piece based on a large language model; the fusion module is used for fusing the document analysis result, the code analysis result and the to-be-tested piece source code to obtain a fused prompt word; a test incentive generation LLM enhancement module generates multiple groups of test incentives according to the fused cue words; and the simulation module obtains the optimal excitation from the multiple groups of test excitation, calls the FPGA simulation test tool, tests the optimal excitation, obtains a test conclusion and a test document, and outputs the optimal excitation, the test conclusion and the test document. The accuracy of the test result and the test efficiency can be improved.

The invention provides a software V-shaped development process oriented RAG retrieval method and system, and the method comprises the steps: receiving a technical document, and carrying out the segmentation and recognition of the document, so as to obtain a document fragment set; extracting an engineering entity, an identifier and an attribute from the document, and constructing a binding relationship between a document fragment and the entity; constructing a knowledge graph containing nodes and node association relationships in a graph database or a triple; constructing a multi-dimensional vector representation of the document fragment, and writing a vector into a vector database; performing semantic retrieval on matched candidate document fragments based on a user query request, and performing neighborhood expansion on the target entity in the knowledge graph to obtain a candidate graph; aligning the candidate document fragments with the candidate atlas, and selecting a preset number of fragments which are ranked in the top to be aggregated into an evidence packet; and inputting the evidence packet and the generation task instruction into a large language model, and generating a retrieval result based on a predetermined constraint decoding strategy. By means of the scheme, the consistency of all stages in RAG retrieval can be guaranteed, and the content retrieval precision is improved.

The invention discloses an archive retrieval method and system based on cloud computing, and the method comprises the steps: obtaining the original data of a drawing document and a technical document through a data collection module of a cloud computing platform, and carrying out the multi-source heterogeneous data fusion, the original data including a CAD drawing, an engineering drawing, a technical specification, a design specification and a product manual.

This application relates to a document generation method, apparatus, device, storage medium, and program product. The method includes: constructing an outline generation prompt text based on a first tree structure composed of the file paths of various technical documents of a target project; generating an outline based on the outline generation prompt text using a large language model to obtain the outline of the technical document for the target project and the chapter description information of each initial chapter in the outline; recursively splitting each initial chapter according to the chapter description information to obtain the chapter content of each sub-chapter under each initial chapter; and generating the technical document for the target project based on the outline and the chapter content of each sub-chapter under each initial chapter. This method can improve the accuracy of generating technical documents for the target project.

The invention discloses an enterprise technical capability assessment method based on document content analysis. The method comprises the following steps: S1, acquiring multi-source technical document data of a to-be-assessed enterprise and preprocessing the multi-source technical document data; s2, carrying out semantic analysis on the preprocessed document data, extracting technical concepts, and mapping the technical concepts to a preset technical field knowledge graph to form structured representation of enterprise technical capabilities; the invention relates to the technical field of enterprise technical capability evaluation. According to the enterprise technical capability assessment method based on document content analysis, a semantic analysis model is adopted to process a standardized document set, technical concept entities are extracted, the semantic similarity between technical concepts and knowledge graph nodes is calculated, the technical concepts meeting the preset conditions are mapped to the corresponding nodes of the knowledge graph, and the technical capability assessment efficiency is improved. The enterprise exclusive technology knowledge graph is formed, key information in the enterprise technology document can be accurately captured, and more reliable technology capability representation is provided for evaluation.

The invention provides a full-link AI deep reasoning container configuration method, which comprises the following steps of: translating original data in an industrial system database by utilizing an AI large model to generate annotation data; constructing an AI agent, wherein the AI agent comprises an AI large model, a knowledge base and a tool set; the knowledge base comprises technical documents and reference data for reasoning; completing the construction of an AI deep reasoning container according to prompt words provided by a user, an AI agent and annotation data; and the AI deep reasoning container is embedded and configured in an industrial system web page, and tasks are periodically processed according to a preset operation cycle and cue words. Through lightweight deployment, close cooperation with existing industrial production systems MES, ERP, WMS and the like of an enterprise can be realized, close cooperation with existing industrial production systems MES, ERP, WMS and the like of the enterprise can be realized, and rapid intelligent upgrading of an original system is realized.