61 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.

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

The 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 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.

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.

This specification provides a technical document question-and-answer pair generation, evaluation, and optimization system and method. The system includes: a document reading module for reading structured technical documents; a multi-level heading parsing module for dividing the technical document into several content blocks according to the document heading hierarchy rules; a question-and-answer generation module for generating questions and answers (question-and-answer pairs) based on the content blocks using natural language processing technology and a large language model; a question-and-answer evaluation module for performing quality scoring and consistency checks on the question-and-answer pairs and outputting evaluation results; a question-and-answer optimization module for optimizing and correcting the question-and-answer pairs based on the evaluation results; and a batch processing and output module for outputting the optimized and corrected question-and-answer pairs using a multi-document batch processing method.

The invention provides a multi-MCU underlying driver code generation method, system and equipment, and the method comprises the steps: building an MCU resource library which comprises a plurality of MCU data folders, and each MCU data folder comprises an engineering template, a technical document and a data warehouse of at least one MCU; obtaining an engineering template and a data warehouse of the target MCU; automatically analyzing a Markdown file in a data warehouse of the target MCU, and generating an interactive underlying driver configuration interface of the target MCU; obtaining user input parameters on the interactive underlying drive configuration interface; and converting the engineering template of the target MCU based on the user input parameter to obtain a bottom drive code of the target MCU. According to the method and the device, the multi-MCU underlying drive codes can be quickly generated, the threshold of developers is reduced, the development time is saved, and the development cost is reduced.

The disclosure relates to a system and method for unsupervised validation of Large Language Model (LLM)-generated outputs. The method includes the steps of receiving input data, which may comprise structured or unstructured text; generating an LLM output based on the input data; extracting a first set of topics from the input data, with each topic represented by a set of keywords; converting the first set of topics into human-readable reference data; extracting a second set of topics from the LLM output; and converting the second set of topics into human-readable candidate data. The method further includes comparing the reference data with the candidate data using one or more performance metrics. Finally, the method determines a validation score based on the comparison results. The disclosed method allows for the objective validation of LLM-generated content, enhancing accuracy and efficiency in diverse applications such as customer service, technical documentation, and legal analysis.

This invention provides a static defect analysis method and system for an agent development framework based on a large language model. The method includes: acquiring the agent development framework to be analyzed and the corresponding downstream applications; extracting the mapping relationship between modules and functions in the agent development framework from its technical documentation and constructing a module-function feature table; acquiring defect-related text describing the defects of the agent development framework in natural language, extracting initial semantic features reflecting the text's thematic structure, and inputting the defect-related text and the initial semantic features into a large language model after vectorization encoding to extract structured defect problems; constructing an abstract syntax tree for each downstream application corresponding to the agent development framework, identifying the actual function calls in each downstream application through the abstract syntax tree, locating the functions and modules associated with the actual defects, and generating static analysis results.

Embodiments automate software discovery and delivery by decoupling repository understanding from change implementation. To aid the product- and technical-discovery phases of the SDLC, a large language model parses source code to produce human-readable technical documentation stored in a documentation store and machine-readable representations comprising vector embeddings linked in a graph store. When product requirements are received via a conversational user interface or a programmatic API, the system generates a change plan. An LLM identifies affected subsystems using graph and similarity queries, composes structured prompts, and conditions automated code transformation tools; communicated through a machine-to-machine orchestration layer (e.g., a Model Context Protocol (MCP) gateway); to generate candidate artifacts. Artifacts are validated by policy gates and packaged as a reviewable change record with documentation, embedding, and graph updates staged in a pre-deployment overlay; upon promotion, the system atomically commits the staged updates. Telemetry from review and deployment informs subsequent planning.

In order to solve the defects in the prior art, the invention provides a ship equipment maintenance support task intelligent planning and aided design method which comprises the following steps: constructing a ship equipment-oriented maintenance support task element system which comprises two aspects of a maintenance support operation sequence and a maintenance support operation attribute; based on a maintenance support task element system oriented to ship equipment, ship equipment maintenance technology documents are collected and marked, and a maintenance support task element graph is constructed. Based on the maintenance support task element graph, nodes of the maintenance support task element graph are subjected to data preprocessing and then serve as learning samples of the graph convolutional neural network to be input into the graph convolutional neural network for model training. And performing intelligent planning and aided design on the compilation of the ship equipment maintenance support task based on the trained model. According to the method, based on the decision normal form of knowledge driving and data driving fusion, the time sequence compliance and the resource adaptability of the operation process are effectively ensured, and technical support is provided for full-life-cycle guarantee of ship equipment.

A system for managing a technical document for a storage device includes: a large language model (LLM) configured to receive parts selected from a first version of the technical document, which have a target characteristic, and a second version of the technical document newer than the first version of the technical document, and generate first vectors for the selected parts from the first version of the technical document and second vectors for all parts from the second version of the technical document based on semantics. A comparator compares each of the second vectors with the first vectors to find a closest first vector, and generates a similarity metric between each of the second vectors and the closest first vector. A classifier classifies each of the parts from the second version of the technical document based on the similarity metric and text values of the parts from the second version.

The invention relates to an automated system for long-term planning and execution of repair works and preventive maintenance, incorporating cost estimation and utilizing artificial intelligence (AI) technologies. The system integrates modules for generating repair schedules and work plans based on technical documentation and regulatory requirements, forecasting repair costs considering market fluctuations and inflation, monitoring actual repair execution, and dynamically adjusting plans in real time. The system implements the integration of technical and financial functionalities within a single platform, providing controlled and segregated access for specialists of various profiles. Additional features include automatic analysis of regulatory documents, market price monitoring, risk management, deviation analysis, occupational safety control, support for a digital technical council, and comprehensive information security compliant with international standards ISO / IEC 27001 and NIST guidelines. The system ensures efficient, accurate, and adaptive repair management and maintenance planning, optimizing resource utilization and reducing operational risks over the long term.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and computing entities for displaying media content of an electrical connector comprising a plurality of pins referenced 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 viewer comprising a first view pane displaying textual information comprising an identifier for the connector and a second view pane displaying media content illustrating the connector and pins; receiving a selection of the identifier; and in response: generating and providing a preview window for the connector comprising pin information; receiving a selection of a pair of pins from the pin information by the user; and in response, causing the pair to be displayed using a highlighting format in the media content, and causing the remaining pins to be displayed in a deemphasized format.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and / or computing entities for displaying content found in technical documentation via an IETM viewer. In accordance with one embodiment, a method is provided comprising: receiving textual changes with respect to a first version of the textual content of the topic; determining an activity level of a user indicative of the user's presence in the topic; based at least in part on the determined activity level of the user: assigning a change format to each of textual changes based at least in part on a change type of each textual change, displaying a change notification comprising an acknowledgement mechanism, and responsive to user interaction with the acknowledgement mechanism, providing a second version of the textual content of the topic, wherein the second version of textual content conveys the textual changes using the change formats assigned to each textual change.

The invention discloses a document verification method and system based on an MCP technology, and the method comprises the following steps: analyzing a technical document through a natural language processing technology, carrying out the atomization decomposition of operation steps in the technical document into a plurality of basic steps, and extracting an expected result of each basic step; constructing an interactive verification scene based on the basic steps; in the interactive verification scene, according to whether the MCP service corresponding to the basic step is found or not, dynamically selecting to be actually executed by the MCP service or to be simulated by the large language model to execute so as to obtain an actual execution result; and comparing the actual execution result with the expected result to generate a verification result. According to the technical document verification method and device, full-process automation of technical document verification is achieved, the verification dimension extends to the operability level from the grammar level, the verification efficiency, accuracy and universality are remarkably improved, and meanwhile the resource cost is reduced.

The invention discloses an automatic document generation method based on hierarchical cue words and a rule engine. The method comprises the following steps: step 1, layered cue word design: completing fine control from document types to specific entries based on multi-level guide design of a framework layer, a chapter layer and an entry layer; 2, designing an intelligent rule engine: designing a rule engine based on a GJB438B / C standard and a domain knowledge base, and realizing logic completeness and compliance verification of document contents to ensure that the contents meet deep requirements of the GJB standard; 3, dynamic generation and optimization driven by a large model: completing natural language demand input processing, multi-objective optimization and negotiation suggestion and change influence analysis based on the semantic understanding capability of the large model LLM; and step 4, output and collaborative management: completing the output of the standardized document, and generating a document conforming to the GJB438B / C standard. The method can be adapted to various military technology documents, uniform standard conformity verification is realized, the change influence report is automatically generated, and the manual coordination cost is reduced.

The invention discloses a T5 pre-training model-based power transmission line crossing frame construction auxiliary generation scheme text retouching method, which comprises the following steps of: constructing a high-quality parallel corpus, and performing multi-task fine tuning on a T5 pre-training model; adopting a term constraint decoding mechanism to carry out retouching processing on the output of the T5 pre-training model; performing standardization compliance inspection through a rule post-processing engine; and generating and outputting a standardized construction scheme. Compared with pure artificial retouching, the method has the advantages that the processing efficiency is remarkably improved, the labor cost is reduced, and compared with a single rule or single statistical method, the method gives consideration to both language fluency and format compliance while ensuring the accuracy, and is easy for engineering deployment and industry popularization; the method is superior to a traditional manual or general AI retouching scheme in the aspects of fidelity, specialty, normalization and auditing performance, unification of construction technology document language quality improvement and production efficiency optimization is achieved, and the method has high practicability and popularization value.

The invention relates to a data lake data quality control method and system based on data rule verification. The method comprises the steps that business and technical documents are analyzed through a large language model, and a data verification rule is automatically generated and stored; executing the rule and collecting a result to a result table; the execution result is compared with a preset reference value, and abnormity is recognized and registered; upstream traceability and downstream influence analysis are carried out on the anomaly based on the metadata blood relationship, and a standardized influence report is generated by using the large language model again; and finally, generating a specific rectification scheme by utilizing the large language model for the third time based on the report. The system comprises corresponding function modules. According to the method, through combination of the large language model and the data blood relationship, full-process automatic and intelligent closed-loop management and control from rule generation, problem discovery, root positioning, influence analysis to scheme suggestion are realized, and the efficiency and accuracy of data quality management are remarkably improved.

This invention provides a domain-adaptive pre-training and fine-tuning method and system for the gas turbine field. The method includes: constructing a multi-source fusion corpus for the gas turbine field, including publicly available standard data, internal technical documents, operation logs and operating condition data, and expert experience knowledge; based on a general large language model, using the corpus for hardware-accelerated domain-adaptive continuous pre-training on a heterogeneous computing platform to obtain a basic model with enhanced domain knowledge. During continuous pre-training, operating condition data is encoded into high-dimensional vectors, fused with the embedding vectors of text tokens, and then input into the model; using a gas turbine field instruction fine-tuning dataset, the basic model is subjected to supervised fine-tuning to obtain a dedicated large language model for the gas turbine field. This addresses the knowledge barriers and performance bottlenecks in industrial applications caused by the high hardware cost of general models and the lack of optimization and adaptation for domestic computing platforms.

This invention relates to the field of large language model dialogue system optimization technology, specifically to a method and system for dynamic dialogue history compression based on dual verification for large language models. The method includes setting the maximum length of the context window, the maximum number of newly generated lexical units, and the size of the safety buffer for the target large language model; loading the dialogue history; initial compression and verification using a keyword and TF-IDF hybrid scoring system; if the requirements are not met, multiple dynamic compressions are performed according to gradients; and finally, when the model generates a response, parameters are adjusted to fit the remaining space. The system includes dialogue history loading, parameter configuration, a dynamic compression engine, and a large language model integration module. Through a multi-level compression verification mechanism and a progressive multi-level dynamic compression strategy, it can handle extremely long texts such as engineering and technical documents, reducing service interruptions, improving compression efficiency while preserving key semantics, and also supporting multilingual dynamic compression. It solves the problems of system token overruns and service instability in existing technologies.

A system for analyzing technical documents for storage devices and extracting multiple-sentence characteristics. The system includes: a plurality of classifiers, each classifier configured to receive multiple sentences from the technical document and generate multi-labels for the multiple sentences, each label indicating whether each sentence has a target characteristic described in the technical document; and an ensemble neural network configured to sequentially receive, as training datasets, multiple multi-labels from the plurality of classifiers, and generate, as a result of training, multiple labels for the multiple sentences based on the training datasets. Each of the plurality of classifiers is configured to receive text fragments at different datapoints corresponding to the multiple sentences with different context window sizes, and generate the multi-labels corresponding to the text fragments.

The invention discloses an agent development platform upgrading compatibility evaluation method and device, a medium and a product, and the method comprises the steps: analyzing a technical document of a target agent development platform to obtain API change information, and storing the change information in an information change library in a structured manner; original process codes of the target agent are obtained, all API calling records are extracted, matching mapping is carried out on the API calling records and the change information in the information change library, and therefore affected API calling and corresponding change types of the API calling are recognized; according to a matching mapping result, calculating an influence score value for each influenced API call, summarizing the influence score values of all the influenced API calls, and performing normalization processing to obtain an overall compatibility influence score value; according to the matching mapping result and the overall compatibility influence score, a compatibility evaluation report is generated, and the technical scheme of the embodiment of the invention can realize automatic, efficient and accurate evaluation of the upgrading compatibility of the intelligent agent development platform.

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.