94 results about "Readability" patented technology

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 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 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.

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.

The application discloses a structured legal document generation method and system based on a large model and a knowledge base enhancement, and belongs to the field of structured legal document generation. The method comprises the following steps: acquiring a case description and a document type according to user input; retrieving a legal regulation knowledge base based on the case description to obtain a relevant law article set related to the case description; retrieving a legal document template knowledge base based on the document type to obtain a legal document template set related to the document type; in the case that there is a legal document template suitable for the case description and consistent with the document type in the legal document template set, generating a legal document of the user input based on the user input, the relevant law article set and the legal document template; otherwise, performing network search according to the document type to generate a structured legal document. The application can improve the readability of the legal document and provide a more intuitive reading experience for the user.

The invention discloses a few-sample readability evaluation method and system, electronic equipment and a storage medium, and belongs to the technical field of natural language processing. The method comprises the steps of obtaining a to-be-evaluated text, and constructing a global prompt with an independent structure and at least one local prompt for the to-be-evaluated text; combining the text with each prompt, inputting the combined text and prompt into a pre-training language model, and extracting global and local prompt feature representations; respectively calculating similarity distribution between each prompt feature representation and a plurality of preset static category prototypes, wherein the static category prototypes are kept fixed in model training; and performing joint modeling on the similarity distribution from different prompts based on a Bayesian probability fusion mechanism, generating fused posterior probability distribution, and determining the readability level of the text according to the fused posterior probability distribution. According to the method, multi-dimensional language features can be effectively modeled, tag semantic fuzziness is properly processed, and high-precision and high-robustness readability evaluation is kept in a few-sample scene.

The invention relates to an official content credibility verification-oriented conditional trigger type text watermarking method, which comprises the following steps of: extracting confidence of a large language model, embedding a hierarchical trigger watermark, dividing a pseudo-random red and green set, detecting statistical characteristics and judging thresholding authenticity. Implicit watermark embedding of an official text and rapid discrimination of a public opinion end are realized. According to the method, the natural readability of the official text and the detectability of the watermark are both considered, the detection Z-score can reach 7.49, the green set hit proportion reaches 69.21%, and the method is suitable for the scenes of government affair document release, news draft clarification, network public opinion management and the like, and has good expansibility and engineering practicability.

The invention discloses a compact family structure text description grammar with high reduction degree. The compact family structure text description grammar comprises a family expression rule and an individual information expression rule. In the family expression rule, parents and children are defined as a group of family members, the parents, the parents and the children and the children are separated by different symbols, and after a group of family data is ended, different symbols are used for expressing ending description. The individual information and the information identifier in the individual information expression rule are respectively expressed by specific characters. The invention defines a structured plain text format for recording family pedigree. The core of the method is to imitate the layout of family trees: intergenerations are vertically distributed, and individuals of the same generation are horizontally aligned. The design has both human readability and machine processability, on one hand, data presentation is clear and visual, and lossless editing by using a text editor is supported; and on the other hand, compared with a traditional format, the data volume of the file is remarkably reduced, and the comfort level of user experience is improved.

The invention provides a dynamic handwriting enhancement method and device based on learning content semantic analysis and electronic equipment, and relates to the technical field of electronic note processing, and the method comprises the steps: obtaining space-time dynamic data corresponding to an original note when a user uses an electronic pen to write; performing stroke unit segmentation on the spatio-temporal dynamic data, and performing feature extraction on the segmented stroke units to obtain a feature tensor of each stroke unit; and performing semantic analysis based on the feature tensor of each stroke unit, determining a target enhancement strategy based on a semantic analysis result, and enhancing the original note based on the target enhancement strategy to obtain an enhanced note. According to the dynamic handwriting enhancement method and device based on learning content semantic analysis and the electronic equipment, by understanding the knowledge essence of the written content, sensing the real-time cognitive state of the user and applying the optimization strategy matched with the knowledge type, the handwriting readability is remarkably improved, and meanwhile the personal writing style is strictly reserved.

The application 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 following steps: obtaining a code pair composed of a source code and a target code from an online programming platform, processing the code pair according to similarity retrieval, fine-grained scoring and differential testing, and constructing a function consistency dataset; performing function learning training on a large model according to the function consistency dataset and an instruction fine-tuning method to obtain the large model trained through the function learning training; obtaining the source code, generating positive sample translation and negative sample translation of the source code, and constructing a style guide dataset; and performing style learning training on the large model trained through the function learning training according to the style guide dataset to obtain a trained code translation large model. The application develops a low-cost and high-efficiency code translation model around a large-scale language model, and enhances the correctness and readability of translated codes.

The invention discloses an operator report PDF exporting method and system, and belongs to the technical field of report generation and document typeset.The method comprises the following steps that a data set and a field name list of a report to be exported are received; dynamically generating a header according to the field name list, and calling a PdfPTable to create a table; for each row of data in the table, estimating the height of the row and comparing the height with the remaining available height of the current page, if the height is not enough, calling document.newPage () for paging, and reconstructing a header on a new page; and for the cells, the Phrase is used for measuring and calculating the text size, and setNoWrap (false) and the minimum height are set so as to realize column width self-adaption and automatic line feed. According to the method, the report export flexibility, attractiveness and readability are remarkably improved, and the multi-scene and multi-format customization requirements of operators are met.

The application discloses an element text processing method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a plurality of description information of a sample object and a sample abstract marked with an element type; extracting an element vector feature of the element type and a description vector feature of each description information; taking the element vector feature and the description vector feature as inputs of a joint abstract model to be trained, and taking the sample abstract as an output of the joint abstract model, wherein the joint abstract model comprises a first model and a second model, and a correlation degree between each description information output by the first model and the element type is an input of the second model, and then the joint abstract model is trained according to a classification loss value of the first model and a decoding loss value of the second model, so as to process commodity description information of a target object to generate a commodity abstract matched with a target element type. The text abstract generated by the method has strong readability, and corresponding text abstracts can be generated according to different element types.

The application discloses a code obfuscation method, an electronic device, a storage medium and a program product, and relates to the technical field of computers. When code obfuscation is needed, a first code is obtained, the first code comprising a plurality of first identifiers; the plurality of first identifiers are subjected to anti-decompilation unrecognizable processing based on a preset mapping table to obtain a second code, the preset mapping table comprising a plurality of corresponding relationships between identifiers and symbols, and the symbols being anti-decompilation unrecognizable symbols; a plurality of reflection code templates without actual functions are determined; and the plurality of reflection code templates are added to the second code to obtain a third code. Through the above method, the first identifiers in the first code can be subjected to anti-decompilation unrecognizable processing according to the preset mapping table, so that the anti-decompilation is erroneous, and the reflection code templates without actual functions can be added, so that the code obtained through anti-decompilation loses readability without affecting normal compilation, and the security of the code is improved.

The invention provides a translation method and a translation system. According to the translation method, firstly, a predefined text knowledge base is adopted to preprocess text segments needing to be precisely processed in a to-be-translated text, so that a prompt of an AI large language model contains a consistent text comparison table customized for the to-be-translated text; wherein fixed translation of specific text segments (such as proper nouns, phrases or sentences) in a to-be-translated text in a target language is defined; and translating the preprocessed text by adopting the AI large language model. The long text such as the novel can be segmented into chapters and sections by adopting an automatic text segmentation technology before translation, and the translated texts of all the chapters and sections are recombined into a target file. According to the technical scheme, the automatic text segmentation technology and a cooperation mechanism of text consistency preprocessing and comparison table guiding type Prompt guidance are combined, the problems of key expression inconsistency, semantic drift and the like occurring in long text translation are effectively avoided, and the continuity and readability of translated texts are improved.

The invention relates to the technical field of networks, in particular to an interpretation language generation method and device suitable for protocol decoding and a medium, and provides an interpretation language suitable for protocol decoding. The method supports the description of logic combination and complex nested structures, has strong expression ability and good readability, is simple enough in design, greatly reduces the manufacturing difficulty and reading difficulty of decoding scripts and the total amount of codes, and greatly shortens the development period. Meanwhile, in protocol decoding, each network protocol is regarded as a formal language, abstraction is carried out to describe most protocols, an interpretation language which is concise in design is designed to standardize and describe basic logic and combination of the formal language, a plain text protocol decoding script is used for replacing a traditional hard coding decoder, and a complete three-level grammar system of words, sentences and segments is constructed.

The invention discloses a code change readability evaluation method based on fine-grained difference perception and enhanced context, and belongs to the crossing field of software engineering and deep learning. The invention constructs a core method for context attention enhancement based on multi-granularity difference representation and difference guidance. Through multi-granularity feature extraction fusing a token level (semantic grammar core change) and a character level (structure details and fine adjustment information), and in combination with a triple context enhancement mechanism of global attention, local attention and similarity attention, accurate judgment of readability change trends (increase / decrease) before and after code change is realized. Experiments on a GitHub open source data set show that the method is remarkably superior to an existing baseline model, readability quality control in a dynamic code evolution scene (such as GitHub warehouse iteration) is effectively supported, and technical support is provided for software maintenance and team cooperation.

A data processing system implements obtaining a first textual content, segmenting the first textual content into a plurality of first segments, and providing each segment of the plurality of first segments to a first natural language processing (NLP) model to obtain a set of first readability scores for the plurality of first segments. The first NLP model is configured to analyze a textual input and to output a readability score representing a measurement of readability of the textual input. The system further implements aggregating the set of first segment readability scores to determine a first readability score for the first textual content, and perform at least one of causing the first readability score to be presented to a user or performing one or more actions on the first textual content based on the readability score.

The application discloses a style visual text editing method, system, device and storage medium, which are corresponding solutions, and the related solutions aim to solve the style consistency problem existing in the image text editing of the existing diffusion model, extract style embedding information from the visual features of the glyph image and the input text image, and input the style embedding information as an enhanced style condition into the diffusion model, so as to realize fine control of the diffusion process, so that the diffusion model can generate a text image with high readability and style consistency, and can realize the keeping of the original text style or style migration based on a reference image.

This invention relates to the field of artificial intelligence technology and discloses a method and system for optimizing and generating audio and video subtitles for less commonly spoken languages. The method includes the following steps: Step 1: Audio extraction and preprocessing; Step 2: Language recognition for the less commonly spoken language; Step 3: Language-aware punctuation restoration module; Step 4: Subtitle readability-driven segmentation module; Step 5: Subtitle format encapsulation and output. This application establishes a complete technical process encompassing audio preprocessing, language-aware speech recognition, structured text restoration, subtitle segmentation optimization, and time alignment. This method significantly improves the accuracy of speech-to-text conversion in less commonly spoken language videos and enhances the structural integrity and readability of subtitles. It is particularly suitable for practical application scenarios involving less commonly spoken languages ​​in regions such as Southeast Asia, where data is scarce and languages ​​are diverse. It has broad application value and practical significance in media dissemination, educational videos, and government services.

The embodiment of the invention discloses a file conversion method and device. The specific embodiment of the method comprises the following steps: detecting the validity of a text file and a list file in response to a received request for converting the text file into the list file; in response to the detection that the text file and the list file are valid, detecting whether the original text content of the original text column of the list file is empty or not; in response to detection that the original text content of the original text column of the list file is not empty, matching the original text content of the original text column of the list file with the original text content of the original text item of the text file; and in response to successful matching, assigning the translation content of the translation item corresponding to the original text content of the original text item of the text file to the translation column of the current row where the original text content of the original text item of the list file is located. According to the embodiment, after the text file is converted into the list file, the data of the list file are clearer in row and column, and the readability is higher. And the content can be paged to facilitate item summarization and statistics. And after the list file is converted into the text file, the error rate is low, and the problems of copying serialization and the like are avoided.

The invention provides an application program data packet generation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a first code of a target application program and at least one target language; wherein the first code uses a first language; the first language is different from the target language; obtaining a to-be-translated character string resource in the first code, translating the to-be-translated character string resource into a target language, and obtaining a target language translation result of the to-be-translated character string resource; updating a to-be-translated character string resource in the first code into a target language translation result to obtain a target code containing the target language translation result; and generating a program data packet of a target language of the target application program based on the target code. According to the mode, the readability and development efficiency of codes are improved, and meanwhile, the program data packet only contains the to-be-translated character string resource of one target language, so that the downloading cost of a user is reduced; when the application program runs, the resource loading and analysis overhead is reduced, and the performance loss is optimized.

The invention relates to a report chart generation method and device based on a multi-modal large model, and the method comprises the steps: obtaining chart drawing data provided by a user through a natural language, calling a first large language model to analyze the chart drawing data, and generating a structured data set; calling the first large language model to generate a chart of an initial version in combination with the structured data set and user requirements; calling a multi-modal generation large model to evaluate and correct the image of the initial version chart to obtain an automatically corrected chart; the user inputs a modification instruction to modify the automatically modified chart to obtain a modified chart; and copying and embedding the modified chart into a specified position of the target report document. Through an original'generation-verification-correction 'closed loop, common problems such as chart layout and label overlapping are automatically detected and corrected by using the multi-modal visual model, the professional quality and readability of the chart are remarkably improved, and manpower is liberated from tedious adjustment.

The application discloses a kind of text readability evaluation method and device, evaluation method is by obtaining target text and historical text library, since historical text library is the text collection of the historical search record of search engine, records the expression habit of conventional word and sentence order, obtains the first scoring standard by the heat of search word in historical text library, to determine whether target text is expressed according to conventional word, obtains the second scoring standard by the sentence vector of search sentence in historical text library, to determine whether target text is expressed according to conventional sentence order, accurately obtains the readability of target text, and then improve the accuracy of text readability evaluation.

The invention provides a hidden attack sample data labeling method, and belongs to the field of artificial intelligence and data security. The method comprises the following steps: firstly, carrying out an attack data labeling process: executing by an attacker, presetting an immune agent by the attacker, effectively interfering a target agent by wrongly written characters generated by the immune agent on the premise of keeping the overall fluency and readability of a text, and meanwhile, ensuring that the target agent is harmless to the own agent; and then carrying out an immune agent detection process. According to the method, interference information such as wrongly written characters and similar characters can be accurately inserted on the basis of ensuring the readability of a text through an intelligent algorithm, so that the purpose of directional attack on a target agent is achieved, and meanwhile, adverse effects on an own agent are effectively avoided; according to the method, hidden labeling of the attack sample can be realized, pollution attack on the target intelligent agent is realized, the influence on the own intelligent agent is avoided, and the method is widely applied to the aspects of poisoning training data, attacking the intelligent agent and the like.

The invention discloses an annotation statement generation method and device, a storage medium and electronic equipment. The method comprises the steps that a target path and an annotation generation option are received, and the annotation generation option is used for indicating attribute information of a target annotation statement; determining file structure information based on the target path, the file structure information being used for determining annotation content of the target annotation statement; and generating a target annotation statement according to the file structure information and the annotation generation option, and inserting the target annotation statement in the target position. The technical problem that code readability is poor due to nonstandard code annotation is solved.

Techniques are disclosed for readability theme generation. The techniques include obtaining reading formats and generating reading format digital images based on the obtained reading formats. The reading format digital images are encoded using a trained machine learning model as perceptual embeddings. The perceptual embeddings are clustered into reading format clusters and readability themes are determined based on the reading format clusters.

Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.

This application discloses a text readability analysis method, system, and electronic device based on NLP processing. The method extracts multiple character entities; performs word segmentation on the preprocessed text to be analyzed to obtain a word sequence and constructs a dependency syntax tree; based on the multiple character entities, the preprocessed text to be analyzed, and the dependency syntax tree, it extracts features such as the number of characters, the entropy of character personality diversity, the conflict density, the dialogue ratio, the relationship density, and the relationship complexity; it processes and fuses these features to obtain a fused feature vector; it inputs the fused feature vector into an encoder to obtain a preliminary score vector; and it determines the readability score of the text to be analyzed based on the preliminary score vector. This application can improve the accuracy of text readability analysis.