183 results about "Readability" patented technology

The invention provides a front-end automatic testing method of a large language model based on LLM, and belongs to the technical field of front-end automatic testing. The method comprises five core steps of test intention recognition and semantic analysis, page structure analysis and target element positioning, automatic generation of a test operation sequence and assertion logic, test script execution and dynamic regression verification, and test feedback analysis and continuous training. The strong semantic understanding and context reasoning capabilities of the LLM are utilized to perform semantic analysis and simulation on a front-end page structure, a user behavior process and business logic, so that automatic generation and maintenance of a test script are realized. According to the method, the test coverage rate and the generation efficiency are greatly improved, the maintenance cost is remarkably reduced, the readability and the intelligence of the test case are enhanced, and the method is suitable for the modern Web front-end application test of rapid iteration.

A computerized-method for comprehensive text-summarization quality-assessment with rank-based normalization and weighted-hierarchical-ranking strategy. The computerized-method includes: (i) receiving an original-text and a summary-text that has been generated by a (GPT)-based LLM that has been provided the original-text and a text-prompt; (ii) operating a text-processing NLP module on the original-text and the summary-text to yield a processed-text of both; (iii) measuring the summary-text to assess text-summarization-quality thereof by operating a plurality of metrics to yield a metric-score; (iv) operating ranked-based normalization on each metric-score to yield a normalized-score; and (v) operating an aggregation based on weighted-hierarchical-ranking strategy of the normalized scores to yield an interpreted final-quality score. The interpreted final-quality score indicates a comprehensive text summarization quality assessment of the summary-text, and the plurality of metrics includes: (i) grammatically; (ii) Flesch-Kincaid (FK) readability; (iii) topic coverage; (iv) compression ratio; (v) cosine similarity; (vi) NER accuracy; (vii) BLEU; and (viii) ROUGE.

The invention belongs to the field of artificial intelligence, and relates to a code conversion method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a source code and a target language; analyzing the source code to generate an abstract syntax tree; analyzing the abstract syntax tree, and extracting semantic information; according to the semantic information and a grammar rule of a target language, converting the code into the target language to obtain a preliminary conversion code; and further optimizing the preliminarily converted code to generate a final translated code. The automation degree is high, and the workload of manual conversion is greatly reduced; the conversion process is standard and unified, and the consistency and accuracy of code conversion are improved; by analyzing the AST, the source code can be understood more deeply, so that the translation code with higher quality is generated; extension and maintenance are easy, and support for new languages or characteristics can be added according to needs; the optimization step ensures that the converted code is not only correct, but also efficient and high in readability; and cross-language programming and code reuse are promoted.

The invention discloses a multi-language text self-adaptive configuration method and electronic equipment, and relates to the technical field of computers, and the method comprises the following steps: obtaining a source text set in response to a translation instruction received when a page runs, and translating the source text set according to a target language identifier and a constraint strategy to obtain a translated text set; according to a constraint strategy, carrying out adaptability detection on each translation in the translation set to obtain an adaptive set and a non-adaptive set; performing semantic rewriting on each non-adaptive translation in the non-adaptive set to obtain a target candidate set; and aggregating the adaptation set and the target candidate set in the same rendering frame, and rendering and displaying the adaptation set and the target candidate set in batches, so that the problems of lack of multi-language dynamic adaptation capability and insufficient semantic equivalent compression are solved, the accumulated layout offset is remarkably reduced on the premise of ensuring semantic integrity and readability, and the layout efficiency is improved. And the page stability and the user experience are improved.

The invention provides a text editing optimization method and device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical field of document editing. According to the specific implementation scheme, a to-be-optimized editing text is obtained, wherein the to-be-optimized editing text comprises a formula character string edited by a user; segmenting the formula character string to obtain a symbol sequence; performing grammatical analysis on the symbol sequence according to a preset grammatical rule to construct an abstract syntax tree; and performing semantic analysis and processing on the abstract syntax tree to obtain an optimized formula character string. According to the method and the device, the syntactic analysis and the semantic analysis are sequentially performed after the formula character string is segmented, so that the code format of the formula character string is automatically adjusted to meet the specification, the optimized character string structure is more rigorous, the layout is clearer, and the readability and the maintainability of the formula character string are improved.

The invention discloses an industrial defect image-text joint detection method and related equipment. The method comprises the following steps: acquiring an industrial product image and extracting multi-scale visual features; obtaining text information related to the image and extracting text features; the image and text features are input into a large language model with a cross-modal attention mechanism for fusion reasoning, and defect semantic features are generated; outputting a pixel-level defect mask through a segmentation decoding module based on the features; and finally, jointly generating defect text description and superposing the defect text description with the original image to form an image-text detection result to be output. The method makes full use of complementarity of visual perception and text knowledge, has the advantages of low sample dependence, high robustness and human readability of output results, is suitable for quality monitoring and defect analysis scenes in the industrial manufacturing process, and has good practicability and popularization value.

The invention belongs to the field of contract document translation, and provides a contract document translation method and system based on a large model, and the method comprises the steps: obtaining a target contract document, recognizing a picture in the target contract document, converting the picture into a text, carrying out the recognition of the text in the target contract document through taking the recognized line feed as a mark of a block, and taking a page number as a maximum unit, the method comprises the following steps of: performing preliminary blocking to form a plurality of text blocks, identifying character features in each block during preliminary blocking, correcting the text blocks according to the identified character features, merging the text blocks belonging to the same natural segment, and splitting the text blocks of incoherent texts; and translating the corrected text blocks by using a pre-trained large model, and writing the translated text blocks into a new file in a form conforming to the character features corresponding to the text blocks to obtain a translated contract document. According to the method, the professionality, correctness and readability of translated documents are improved.

The invention discloses a code annotation generation method and device, electronic equipment, a storage medium and a product, which are applied to the technical field of computers and are used for solving the problem of low efficiency caused by manual annotation writing in the prior art and effectively ensuring the accuracy and practicability of annotation so as to improve the readability of codes. Determining an annotation prompting rule; the annotation prompting rule comprises a corresponding relation between a code statement type and a code annotation type; analyzing the target program code by utilizing a large language model, and determining a to-be-annotated code snippet in the target program code and semantic information and a statement type of the to-be-annotated code snippet; determining an annotation type corresponding to the to-be-annotated code snippet according to an annotation prompt rule and the statement type of the to-be-annotated code snippet; and generating a target annotation text corresponding to the to-be-annotated code snippet according to the annotation type and semantic information corresponding to the to-be-annotated code snippet, and inserting the target annotation text into an annotation position corresponding to the to-be-annotated code snippet.

A method for extracting key phrases based on extracting both informative and readable phrases from documents. The method includes separating documents into sentences to extract sentence-level phrases and separating the documents into segments of a fixed length to extract segment-level phrases. The method further includes using a PMI and entropy model to also extract readable phrases from the documents. The method includes comparing the sentence-level phrases, the segment-level phrases, and the readable phrases to generate key phrases for the documents.

The invention provides a digital watermark embedding and detecting method, equipment and a medium, and aims to solve the problems of easy perception, opaqueness and low robustness of the existing text digital watermark technology. The method comprises the steps that an Nth target clause is predicted, and at least two (N + 1) th candidate clauses are generated; according to the Nth target clause and a preset first watermark feature coding sequence, a first watermark feature coding value of an (N + 1) th target clause is determined, and the (N + 1) th target clause is the next clause of the Nth target clause; determining the (N + 1) th target clause according to the prediction probability of the at least two (N + 1) th candidate clauses, the first watermark feature coding value and a preset readability threshold; under the condition that the N + 1 target clauses comprise text end characters, a full text embedded with watermarks is determined, the full text embedded with watermarks comprises the N + 1 target clauses, and N is an integer larger than 0. According to the invention, low perception, transparency and robustness of digital watermark embedding can be realized.

The invention discloses a sign language translation system and method based on lightweight mask enhancement, and the method comprises the following steps: 1, employing an inter-frame difference technology to recognize and reject redundant frames having no substantial contribution to motion expression, and further distinguishing the foreground and background information of sign language motion through a local dynamic mask module; step 2, inputting the sign language video optimized by the lightweight mask module to a visual module; accurate and comprehensive visual features are generated; 3, converting the visual features obtained from the visual module into language features suitable for language processing; and step 4, the language module receives the language features converted by the mapping module, and processes the language features in combination with an encoder-decoder model mBART to improve the quality of the output text. According to the method, the accuracy and efficiency of sign language-to-spoken language translation are remarkably improved; the method not only optimizes the use of computing resources, but also greatly enhances the readability and semantic coherence of translation results, and provides powerful technical support for realizing more popular and convenient sign language communication.

The invention provides a large model code translation method and device fusing code functions and styles, and relates to the technical field of natural language processing. The method comprises the steps that code pairs composed of source codes and target codes are obtained from an online programming platform, the code pairs are processed according to similarity retrieval, fine granularity scoring and difference testing, and a function consistency data set is constructed; performing functional learning training on the large model according to the functional consistency data set and an instruction fine tuning method to obtain a large model subjected to functional learning training; obtaining a source code, generating positive sample translation and negative sample translation of the source code, and constructing a style-oriented data set; and according to the style-oriented data set, style learning training is carried out on the large model subjected to function learning training, and a trained code translation large model is obtained. According to the method, a low-cost and high-efficiency code translation model is developed around a large-scale language model, and the correctness and readability of translated codes are enhanced.

The invention belongs to the technical field of information retrieval, and particularly relates to a library document abstract generation method based on deep learning model construction, which comprises the steps of data preprocessing, model construction, semantic understanding and core viewpoint extraction, abstract generation and optimization and quality evaluation. According to the library literature abstract generation method based on deep learning model construction, the mixed labeling technology is combined with rules and deep learning, the advantages of the rules and the deep learning are fully played, the rules provide a basic framework, the deep learning makes up for the deficiencies of the rules, and domain term meanings can be more accurately understood; the domain entity knowledge base ensures accurate recognition and relation understanding of entities in literatures through a rigorous extraction and disambiguation method, a foundation is laid for high-quality abstract generation from the semantic level, and in addition, through accurate understanding of domain terms and effective capture of long text semantic association, the abstract generation efficiency is improved. The accuracy, the integrity and the readability of the generated abstract are improved, so that the requirement of a user for quickly acquiring the key information of the literature is better met.

The invention discloses a large model generation code watermarking method based on equivalent semantic transformation, a program, equipment and a storage medium, and belongs to the technical field of digital technology watermarking. According to the method, the equivalence principle of code semantic conversion is adopted, a conversion rule suitable for the generated code is designed, and the watermark is embedded into the generated code according to a certain coding rule by utilizing the rule. According to the method, the code generation model does not need to be retrained or finely adjusted, only the generated code needs to be post-processed, good cross-model compatibility is shown, and meanwhile, the watermark embedding efficiency is guaranteed. The method has the rapid watermark processing capacity, code watermark embedding can be completed in a short time, and the processing efficiency in practical application is greatly improved. Due to the fact that the equivalent semantic conversion mode is adopted, no negative influence is generated on the quality of the codes, and normal functions of the codes and readability of the codes are guaranteed.

A pre-training language model-based summarization generation method, including: acquiring text information of a summarization to be generated, and performing multi-feature weighted language pre-training processing on the text information to obtain a candidate summarization; inputting the candidate summarization into a pre-training language model to obtain output data of the pre-training language model; and inputting the output data of the pre-training language model into a decoder model to obtain a target summarization. The pre-training processing is performed on the text information of the summarization to be generated, and then the target summarization can be generated after processing performed by an encoder and a decoder, improving the quality and readability of the summarization.

The invention discloses an optimization method and device for a natural language processing model, and relates to the technical field of information security, and the method comprises the steps: reducing the text confusion degree through employing an iterative beam search mode, and guaranteeing the text quality at the same time, i.e., carrying out the quantitative evaluation and screening of readability and usefulness in a processing process, and improving the processing efficiency. And performing model fine tuning by using the optimized and transformed mixed data to reduce the influence of harmful texts in the third-party data on the model security alignment, thereby improving the security performance and the alignment degree of the large model, and solving the problem that the security alignment of the large language model cannot be effectively coped with in the related technology, and the security alignment efficiency is improved. The technical problem that possible harmful information damage in the third-party data is difficult to fundamentally reduce is solved, and the technical effects that the safety performance and the alignment degree of the large language model are improved, it is ensured that the large language model can give safe and reliable response when facing the data safety problem, and harmful information is prevented from being provided are achieved.

The invention relates to a code annotation information processing method and device, computer equipment and a storage medium, and belongs to the technical field of code detection. Evaluating the complexity of the code, and determining a complex code according to an evaluation result; obtaining first code annotation information corresponding to the complex code, and preprocessing the first code annotation information to obtain target code annotation information; performing syntactic analysis on the target code annotation information to obtain a syntactic analysis result; and determining and complementing missing information in the target code annotation information according to a syntactic analysis result. According to the method, the completeness and accuracy of the annotation information of the complex code can be remarkably improved, the annotation content is more coherent and clearer, the readability of the complex code is improved, the time of manually compiling and revising the annotation information of the complex code by developers is shortened, and the efficiency of the overall development process is improved.

The invention discloses a code static review method and system based on a fine tuning large language model, and belongs to the technical field of software static testing. The method comprises the steps that a code static rule set is collected and preprocessed, standard rules are screened according to programming languages and project requirements, and grading classification and duplicate removal are carried out; the method comprises the following steps: constructing a positive and negative example program data set in three modes of open source code analysis, fault implantation and large language model generation, and integrating into structured training data in combination with a template; selecting a base model matched with a code reasoning task, optimizing model parameters by adopting a LoRA fine tuning method, and predicting code rule violation conditions through output layer design; and evaluating model performance based on the indexes. According to the method, the efficiency of static review is enhanced, including readability, friendly interaction and expandability of reports, false reports and missing reports are reduced by improving the ability of code context understanding, and cross-language and cross-platform portability is realized.

The invention relates to the technical field of data analysis, and discloses an event context generation method and device, computer equipment and a storage medium, and aims to analyze theme description information, recommend synonyms and generate a keyword list through a large language model, simplify the operation difficulty of clients and improve the data comprehensiveness. According to the method, the news data are collected through the logic expression corresponding to the keyword list, the time feature text in the news data is standardized, the target short sentence only containing the standard time is obtained, the standard time corresponding to various texts is deduced through the context reasoning ability of the large language model, and the data recall rate and accuracy are improved. The target short sentences are grouped and clustered by using a large language model vector, so that the merging capability of similar events is improved. And selecting the core short sentences of each cluster to generate event sequence data, processing the event sequence data in combination with a logic expression, and filtering uncorrelated events. And finally, generating event venation with high readability by utilizing text output and summarization capability of the large language model.

The invention discloses an intelligent document desensitization tool and method based on deep learning. The method comprises the following steps: converting a Word document to be processed into structured data; recording the type, the position and the context environment of the sensitive information through a deep learning model and a natural language processing technology, and analyzing and judging the function and the importance of the recognized sensitive information in a document by utilizing the trained deep learning model; selecting matched alternative words or phrases from the virtual element library to carry out unified replacement on the semantic elements needing to keep the context consistency, so as to ensure the continuity and logicality of the text; comparing the structured data before and after desensitization to ensure that the related sensitive information is correctly processed; and meanwhile, the readability and semantic coherence of the desensitized text are evaluated by utilizing a natural language understanding technology. According to the method, increasingly complicated privacy protection challenges can be effectively handled, and the potential value of data can be fully mined and utilized.

The present invention relates to the technical field of data security, and in particular to an adaptive masking method and system, and a device and a medium. The method comprises: firstly, acquiring a keyword of a current file to be masked of a sender user; then, on the basis of the keyword, performing addition, deletion and modification on a current sensitive word library to obtain a new sensitive word library; and finally, generating a regular expression on the basis of the new sensitive word library, determining the positions of sensitive words on the basis of the regular expression, so as to obtain the sensitive words, and performing masking to obtain a masked file. Therefore, masking of a plurality of types of data is realized, and data types before and after masking remain unchanged, thereby ensuring the readability of a masked file while guaranteeing the security of masked data, and further increasing the masking speed; on the basis of different roles of receiver and sender users, the masking intensity is adaptively selected, thereby preventing important information from being leaked to untrusted persons, and overcoming the defect of an existing masking algorithm failing to resist collusion attacks and brute-force enumeration attacks; and multiple threads are used to concurrently process sensitive word retrieval and sensitive-word masking operations, thereby greatly increasing the masking speed.

The invention discloses a test case editing scheme oriented to the automatic test industry, and the scheme realizes efficient editing, analysis and execution of test cases through layered architecture design. The scheme comprises the following steps: (1) dividing a test case into a measurement abstraction layer and a hardware abstraction layer; (2) in the measurement abstraction layer, constructing a test index sequence and a corresponding index operation sequence to form a test process file; (3) in the hardware abstraction layer, establishing a mapping relation between the operation keyword and the underlying instrument driver, and forming an instrument configuration file; and (4) the test process file and the instrument configuration file are converted into objectified description, so that flexible editing and automatic script conversion of the test case are realized. The method has the beneficial effects that (1) the readability and editing efficiency of the test case are improved, and the workload of manual script conversion is reduced; (2) the generalization ability of the test scheme is enhanced, and the method is suitable for various test devices and test scenes; and (3) flexible configuration and efficient reuse of test resources are realized through a layered architecture and a standardized file format.

The invention provides a text readability classification method, system and device based on comparative learning and a medium, and relates to the field of natural language process.The method comprises the steps that an obtained first target text is input into a preset BERT model, each word in the first target text is converted into vector representation through word embedding, and a plurality of word vectors are obtained; encoding the plurality of word vectors to determine an initial feature vector; extracting the most important word information of each token through maximum pooling to obtain a word level feature vector sequence; and training the model based on comparative learning to obtain a mature target classifier. According to the method, a comparative learning framework training model is introduced, the understanding of the whole sentence and the coding of semantic information are considered in the training process, and the detail information of the word level is also considered, so that the recognition capability of the model on the readability nuisance is enhanced; the general representation of the text is learned based on comparative learning, and the transportability of the feature set of the model in different data sets and application scenes is improved.

Methods and devices (DV) for rescaling text blocks to maintain readability are disclosed. In a display area (5) an initial text block enclosed in an initial container including a block handle is displayed. In an input area, a user interaction gesture over the block handle is detected. The initial container height is resized according to the user interaction gesture. An updated interline ratio is determined in response to said resizing. An updated font size is determined in response to said determining of the updated interline ratio. Finally, an updated text block including the updated interline ratio and the updated font size according to the resized container is displayed.

The invention provides an automatic wrong question typesetting method, a printer and a learning system, and relates to the technical field of education, the method combines a binding demand with a typesetting scheme, so that the obtained target typesetting scheme can adapt to subsequent binding operation, the problem that a user reads difficultly due to the fact that a question is shielded by binding is avoided, and binding robustness is enhanced. Moreover, according to the method, the target typesetting scheme is jointly generated in combination with the content features of all the questions in the printing task, the printing paper features, the analysis result and the binding demand information, typesetting automation can be achieved, a user does not need to arrange typesetting manually, human errors are reduced, typesetting efficiency and the content adaptability of typesetting pages are improved, and the typesetting efficiency is improved. The typesetting quality is improved, cognitive errors caused by typesetting disorder of the user are reduced, and the readability is enhanced. Moreover, the paper utilization rate can be increased, and resource waste is avoided. In addition, the analysis result is introduced, so that the target typesetting scheme of the printing task is more comprehensive and more targeted, and the user experience is improved.

The embodiment of the invention discloses a teaching note generation method and device based on a large language model and a medium, belongs to the technical field of artificial intelligence, and solves the problems that classroom notes generated in the prior art are lack of content structuring and knowledge relevance, poor in readability and difficult to be used for effective review. The method comprises the following steps: acquiring a teacher voice signal in a classroom teaching environment in real time through pickup equipment, and converting the teacher voice signal into an initial text stream through a preset voice recognition model; taking the initial text flow as query input, and performing semantic similarity retrieval on the initial text flow and a preset course knowledge base to obtain a plurality of related knowledge fragments; generating an enhanced prompt based on the initial text stream and the plurality of related knowledge fragments, and generating a structured classroom note based on the enhanced prompt and a preset large language model; and outputting the structured classroom note to a user interface, and optimizing a classroom teaching note generation process based on feedback information and modification information of the user.

The present application relates to the field of text detection technology, and in particular to a text detection method and system. The method comprises: obtaining text usage requirements; obtaining rich text historical archives based on the text usage requirements; parsing the rich text historical archives to determine structured multi-type rich texts; determining detection requirement-oriented information based on the text usage requirements and the structured multi-type rich texts; judging whether there is multimedia fusion content in the detection requirement-oriented information; if so, determining the detection result information set based on the multimedia fusion content; and outputting the detection result information set as a structured text. This ensures the accuracy and reliability of data and reduces the interference of irrelevant data; makes information more convenient for data analysis and processing, improves the practical value of information, makes the detection result information set readable and understandable, facilitates users to quickly obtain information, facilitates computer processing and analysis, and provides support for subsequent data mining and application.

A context-aware AI-supported writing assistance system (100) that includes the following: a natural language processing (NLP) module configured to analyze and process the input text for grammar, syntax, and semantic accuracy; a context recognition module configured to identify the writing intent, scope, audience, and tone of the input text; an adaptive recommendation module based on machine learning, configured to learn from user interactions and refine writing suggestions over time; a module for optimizing sentence coherence and logical flow, configured to ensure structural consistency and improve the readability of the entire document; a module for analyzing tone and mood, configured to evaluate and adjust the written tone based on the intended audience and purpose; a module for plagiarism detection and originality assurance, configured to check for duplicate content and provide rewriting recommendations; and an integration module configured to enable connectivity with document editors, cloud-based applications and the content management system (100).

This disclosure proposes a dialogue processing method, a training method for a question rewriting model, and a device thereof. The dialogue processing method includes: when information is missing in the user question, inputting the user question and historical dialogue content into the encoding layer of the question rewriting model to obtain the semantic representation vectors of each word in the historical dialogue content and the semantic representation vectors of each word in the user question, as well as the keyword scores of each word in the historical dialogue content; then, the decoding layer accurately selects keywords semantically related to the user question from the historical dialogue content based on the semantic representation vectors of each word in the user question, the semantic representation vectors of each word in the historical dialogue content, and the keyword scores, and explicitly generates a fully rewritten user question based on these keywords. This accurately supplements the missing information in the user question, achieving completeness and readability of the user question content and improving the user experience.

The embodiment of the invention provides a note generation method and device and computer equipment. The note generation method comprises the following steps: performing voice recognition on data of a guidance process to obtain text data; extracting a guidance summary according to the text data; retrieving extension information associated with the guidance summary; and generating a note of the guidance process according to the expansion information and the guidance summary. According to the embodiment of the invention, the readability and practicability of the generated notes can be improved.