1100 results about "HTML" patented technology

This invention provides a web application system that allows instructors to effectively use generative AI in classes to match learning tasks, reducing the risk of students asking questions that are inappropriate for the task or trusting false information from the generative AI, and encouraging students' creative thinking through dialogue using generative AI, with the aim of supporting creative activities. SOLUTION: The web application system of this invention creates prompts by integrating questions from learners with prompts preset by the instructor, and provides automatically generated answers through API connection. The app is built using HTML code with a website creation tool, so it can be managed without specialized knowledge. Prompts are edited using three items: Theme, Conditions, and Additional Instructions, to control the answers of the generating AI. In addition, restrictions on questions outside the topic can be set to prevent misuse.

The invention provides a Web application fuzzy testing method based on a multi-modal large model assisted web crawler, which comprises the following steps of: collecting page information of a Web application program by using an LLM (Logical Link Model), extracting associated information among Web pages, and constructing a state machine according to the associated information among the Web pages to guide a sequence of crawling the Web pages; performing screenshot on the Web page by using the MLLM, obtaining HTML (Hypertext Markup Language) content of the Web page, and generating a natural language description of a task so as to describe the task needing to be completed by a user on the page and an operation required for completing the task; and sequentially converting the natural language description into test codes by using LLM, judging whether the test codes successfully complete a task or not according to the state change of the Web page before and after execution, and if the test codes successfully complete the task, generating corresponding form content and an operation sequence to generate an effective HTTP request. The method has the advantages of simple implementation method, low cost, high test efficiency, high coverage rate and the like.

The invention belongs to the technical field of webpage data analysis, and particularly relates to a webpage data analysis method based on a large language model, which comprises the following steps: acquiring a target website URL (Uniform Resource Locator) input by a user; carrying out preliminary analysis on the input URL by utilizing a large language model; the DOM structure of each website is analyzed, and HTML elements and the hierarchical relation thereof are extracted; generating a corresponding data crawling script according to an analysis result; executing the data crawling script, and extracting required data from each website; the extracted data is preprocessed; performing multi-source fusion on the preprocessed data; extracting main information from the fused data; and storing the finally processed and extracted information in a database. According to the method, automatic analysis of complex webpage data, intelligent entity extraction and knowledge expansion and efficient data fusion and duplicate removal are realized.

HyperText Markup Language (HTML) content analysis (HCA) using machine learning is described. A feature vector schema may be generated based on domain names corresponding to HTML webpages and corresponding indications of a status of the HTML webpage. The schema may map each position in a feature vector of a given HTML webpage to a resource identifier. Information may be processed using the schema to generate respective feature vectors. The feature vectors may be used to train a model to generate risk indicators for HTML webpages. A potentially parked domain webpage or a potentially malicious domain webpage may be received. A feature vector for the webpage may be generated and inputted to the model. The model may generate a risk indicator for the webpage. The risk indicator may be output and may cause responsive actions. The model may be updated based on a determination indicating whether the webpage was a parked domain webpage or a malicious domain webpage.

Machine learning models for autonomously navigating the web and / or apps are provided that receive (i) visual input that includes one or more images representing the current, and optionally one or more prior, visual states of the website or app being navigated, and (ii) textual input that represents a user request to be implemented by the model, the current HTML or other code defining the website or app, and optionally additional text like prior model outputs that represent prior steps in the navigation of the website or app by the model. The visual input and textual input are transformed into respective sets of visual and textual tokens, and this multi-modal token set is applied to an encoder. The output of the encoder is applied to a decoder to generate textual output that represents an action to take, relative to the code defining the website or app, to pursue the user request.

The invention discloses a method and device for achieving intelligent AI webpage content obtaining based on LLM, a storage medium and a program product, and relates to the technical field of data processing. According to the method, the search instruction input by the user is received, the search instruction is input into the trained semantic analysis model, after the semantic analysis model converts the search instruction into the query parameter, the query parameter is sent to the search engine, then the webpage obtained by the search engine according to the query parameter is received, and the search result is obtained. The method comprises the following steps: acquiring a webpage, determining a target webpage from the webpage according to a preset screening rule, crawling an HTML (Hypertext Markup Language) source code of the target webpage based on a pre-acquired authorization result, inputting the HTML source code into a trained LLM model, and determining a target code label in the LLM model according to the HTML source code to obtain text content in the target code label. Wherein the LLM model has a strong language understanding capability and can dynamically adapt to the change of a webpage structure, so that the time cost of crawling webpage contents is reduced.

Disclosed herein are systems and method for reference-based detection of phishing webpages. In one aspect, a method includes inputting, for a webpage with a first domain, (1) textual data into a machine learning model (MLM) that outputs a first vector with probabilities of the textual data being associated with known brands, (2) HTML data into an MLM that outputs a second vector with probabilities of the HTML data being associated with the known brands, (3) at least one image into an MLM that outputs a third vector with probabilities of the at least one image being associated with the known brands. The model may input the first, second, and third vectors into an MLM that outputs a brand of the webpage. The method may block the webpage in response to determining that the first domain of the webpage does not match at least one domain corresponding to the brand.

The invention discloses a multi-format document table data extraction and alignment method based on a large language model, which comprises the following steps of: performing table extraction on an editable document / non-editable document to obtain a table in an HTML (Hypertext Markup Language) format; the tables in the HTML format are analyzed based on a large language model, and useful tables are screened out; and aligning the screened useful tables according to set standard fields by adopting a large language model. According to the method, the problem of table data alignment standardization based on manual rules is converted into the problem of data extraction and alignment standardization based on semantic recognition of a large language model, the problems of super-long tables, cross-page tables and table formatting in various types of documents can be effectively solved, complete tables are extracted, and standardized field storage of the tables is achieved.

The invention relates to a cross-frame compatible method based on an existing component, which comprises the following steps of: extracting a functional component in an existing front-end frame, separating and packaging business logic and a UI (User Interface) component in an independent project, and abstracting an interface and a method irrelevant to the frame, so that the functional component can be loaded and run in different front-end frames. And packaging the functional component to generate an independent JS file and a resource file, combining the JS file and the resource file into an HTML (Hypertext Markup Language) page to generate an online access link, and embedding the online access link into a target front-end framework to run. Meanwhile, a standardized communication interface is utilized to realize two-way communication between functional components in the host framework and the target framework, and business data transmission and event interaction are carried out. According to the invention, through packaging of the functional component and standardization processing of the abstract interface, the problem that the functional component is difficult to reuse in different frames in the prior art is solved, and the functional component can be flexibly deployed and operated in multiple frames, so that the development workload is reduced, and the expansibility and maintenance efficiency of the system are improved.

The invention relates to a PPT file content extraction method and system based on a large language model, electronic equipment and a storage medium. The PPT file content extraction method comprises the steps that a PPT file is obtained through a crawler, and a video processing tool extracts PPT key frames and audio-to-text in a video; pPT image processing relates to enhancement, segmentation, OCR and object detection; the large language model application covers a multi-modal input layer, a vision-language fusion network and model fine tuning; and converting the PPT and video PPT data into HTML (Hypertext Markup Language) files. Compared with a PPT file processing method in the related technology, the method can automatically generate data required by large model training in batches. A large number of high-quality structured data sets are provided, the large model can better learn features and rules of PPT content, detailed text description can be generated according to visual information of PPT, PPT description is improved to be more accurate, and the quality of the data sets is higher.

The invention discloses an RPA code generation method based on an HTML and an image, and the method comprises the following steps: S1, receiving multi-modal input data provided by a user, the multi-modal input data comprising an HTML structure file of a target business system, an interface screenshot image and a natural language operation demand description; s2, performing standardized analysis on the HTML structure file, extracting DOM tree structure information, and performing visual feature enhancement processing on the interface screenshot image; and S3, inputting the processed HTML structure information, the interface screenshot image and the natural language operation requirement into a pre-trained visual language model, and outputting a target XPath path and a Python code sequence through the visual language model. According to the method, comprehensive understanding of a complex service system is realized by combining HTML structure information and an interface image, so that efficient and accurate RPA script codes capable of being executed on multiple platforms are automatically generated.

The invention discloses a page rendering method, a page rendering device, electronic equipment and a readable storage medium, the method comprises the steps that a document object model tree is constructed by analyzing a source code of a target page, and each HTML tag in the source code corresponds to an object node in the document object model tree; a document structure tree is constructed by analyzing the document object model tree, the document structure tree comprises document nodes and partition nodes, each partition node comprises at least one paragraph node, each paragraph node comprises at least one content node, and each content node comprises at least one content node; the document node, the partition node, the paragraph node and the content node all comprise node control information; and performing page rendering according to the document structure tree.

The invention discloses an automatic financial data collection system based on a web crawler technology. The system comprises an intelligent crawler collection module, a financial data processing module and a data collection module. The intelligent crawler acquisition module comprises a dynamic scheduling crawler cluster unit, a multi-format capture engine and a metadata marking unit; the dynamic scheduling crawler cluster configures a routing algorithm based on reinforcement learning, and dynamically adjusts an IP proxy strategy through an anti-crawling feature matrix; the multi-format capture engine is integrated with a PDF / HTML / JSON heterogeneous data analysis channel; the metadata marking unit generates a data source label by adopting multi-layer coding conversion; and the financial data processing module comprises a cross-format analyzer, a data cleaning pipeline and a structured storage unit. According to the scheme, through innovative designs such as multi-modal data analysis, self-adaptive anti-creeping confrontation, dynamic resource scheduling and intelligent association analysis, the core problems of low heterogeneous data integration efficiency, weak dynamic anti-creeping confrontation capability and the like are solved.

The invention discloses an HTML (Hypertext Markup Language) information extraction method and device based on a multi-LoRA cascade strategy, equipment and a medium, and relates to the technical field of HTML information extraction. The information extraction method comprises the following steps: acquiring a document and inputting a large language model; and the large language model judges whether a table is included. And if the table is included, calling a table processing LoRA adapter to extract table content and convert the table content into pseudo natural language description, calling a text processing logic module to extract adjacent text contexts of the table, and then performing semantic integration to obtain first text information. And if the table is not included, calling a text processing module of the table processing LoRA adapter to extract the text content, and obtaining the first text information. And calling a key information extraction LoRA adapter, and extracting the structured key value pair from the first text information to generate JSON data. And calling a nested structured generation module to convert the JSON data into a target sequence in a multi-layer nested JSON format.

The invention provides a universal Web form generation method and system based on iReport, and relates to the technical field of computer software, and the method comprises the following steps: obtaining document information, identifying metadata information of a document, defining attribute information of the metadata information, and obtaining a structured metadata definition set; according to the metadata definition set and a form design function of i Report, performing arrangement and attribute mapping processing on each object in a preset form basic interface to obtain a form design template with a mapping relationship between an interface control and a corresponding document attribute; according to the form design template, respectively calling a Web control rendering engine and a PDF generation function of iReport, and carrying out page control or file template rendering processing to obtain an HTML page and / or a PDF file for a user to input Web data; and according to the HTML page, carrying out user data entry and verification processing to obtain standardized form data. According to the method, the editable Web page can be quickly generated, and the corresponding standardized PDF file can also be generated.

The present application describes systems and methods for analyzing hypertext. An element detector receives input information (e.g., hypertext) that is included in a web page. The element detector identifies one or more elements in the input information that are relevant to a classification task. The classification task may include classifying the one or more elements. An element extractor generates text tokens, positional tokens, and / or path tokens based on the identified one or more elements. A machine learning (ML) model outputs one or more vector representations based on the text tokens, positional tokens, and / or path tokens. An output classifier, which may be an additional layer of the ML model, classifies the one or more elements into classifications based on the one or more vector representations. A tool may perform one or more tasks based on the classifications.

The invention relates to a UI automatic testing method and system.The method comprises the steps that interface elements are obtained according to HTML source codes of a prototype interface, element keywords of the interface elements are obtained according to the element types of the interface elements, and when the interface elements contain click events, testing logic of the click events can be automatically recorded and tracked; and associating the element keyword with the test logic to establish a mapping relationship between the test logic and the interface element, constructing a to-be-tested demand description according to the element type and the mapping relationship, and inputting the to-be-tested demand description into the AI large language model to generate a UI automatic test script. And performing UI automatic testing on the to-be-tested interface corresponding to the prototype interface according to the UI automatic testing script to obtain a testing result. Therefore, when the interface layout of the to-be-tested interface is changed, the interface elements can be positioned through the element keywords, the associated test logic is further driven, the UI automatic test script does not need to be modified and maintained, and the UI automatic test efficiency is improved.

The invention relates to the technical field of data processing, in particular to an HTML (Hypertext Markup Language)-based webpage word cutting annotation generation method, system and equipment, and aims to solve the problems of low storage efficiency, poor dynamic webpage adaptability, lack of fault tolerance and insufficient cross-browser compatibility of an existing word cutting annotation method. The method comprises the steps of capturing a selected area; obtaining DOM node path data and text offset, and generating positioning data; recursively storing the path data to generate a unique fingerprint identifier; storing the fingerprint data as historical fingerprint data in a JSON format; performing matching and positioning based on the historical fingerprint data; and mapping information in the historical fingerprint data to an HTML page to realize bidirectional rendering. According to the method, the label name, the class name and the hierarchical relationship of the DOM node are recorded through the node path to construct the fingerprint identifier, and cross-platform data exchange is realized through the JSON structure, so that webpage labeling which is efficient, accurate, high in fault tolerance and adaptive to a dynamic page is realized.

The present invention discloses a method for transparent transmission of byte of Internet of Things based on H5JS local programming, fully explores the potential application characteristics of cloud Internet of Things MQTT combined with Nodemcu, and establishes a local operation mode of Html-JS program on a mobile terminal (referring to a mobile phone or a computer) with full-range byte transparent transmission as the basis of network communication. It is proposed that cloud Internet of Things MQTT supplements the direct WeChat and sound alarm functions, and provides a local execution of Internet of Things Html-JS general program, which not only greatly reduces the user programming links, avoids low-level repetition, but also provides programming examples. Because this mode is also particularly suitable for combining with a single-chip microcomputer, and MQTT is not required in a local area network. At the same time, it is also proposed that the Nodemcu program migrates to JS or realizes program minimization through reset, as well as high-speed timing sampling, and uses a single-chip microcomputer combined with ESP-12 to batch and centrally transmit data to a mobile terminal mode connected to wifi. Such a streamlined and complete Internet of Things, from local area network to wide area network, from computer mobile phone connection to single-chip microcomputer to send WeChat, adopts mainstream technology, and is very suitable for use as a unified textbook of Internet of Things for colleges and universities.

The invention provides a water conservancy knowledge structured extraction and verification method and device, and belongs to the technical field of artificial intelligence, and the method comprises the steps: carrying out the differential text processing of different formats of files, and generating an intermediate file; classifying the intermediate file into a regulation class or a non-regulation class based on a preset rule base; performing hierarchical title identification on the regulatory files to form entry knowledge blocks, and converting table contents into HTML (Hypertext Markup Language) knowledge blocks; performing semantic segmentation on the non-regulation file to generate knowledge blocks; performing knowledge block checking and filing, and marking an abnormal alarm block; converting the table knowledge blocks into natural language description by utilizing a large model; and positioning the context of the original text of the alarm knowledge block, and performing intelligent correction through a large model. According to the method, a traditional semantic analysis model and a large language model are creatively fused, a closed-loop process of preprocessing, extraction, verification and correction is formed, the problems of structured analysis and error correction of complex texts in the water conservancy field are solved, and the knowledge processing efficiency and accuracy are remarkably improved.

Described are systems and methods for generating protected accessible HyperText Markup Language (“HTML”), the method including receiving a request to load media content associated with a first HTML element, upon receiving the request to load the content element, generating video data associated with the content element, generating one or more digital rights management-protected files based on the video data associated with the content element, generating a second HTML element based on the one or more DRM-protected files, and causing to output, via a graphical user interface, the digital rights management-protected video data of the second HTML element.

The invention discloses a method and a system for realizing hosted API automatic testing by an API gateway, belongs to the technical field of computer software, and aims at solving the technical problems of how to realize non-intrusive and automatic API testing, ensuring that monitoring and verification can be directly carried out on an API flow level, improving the testing efficiency and the coverage rate and improving the testing efficiency. According to the technical scheme, the method comprises the steps of test case generation, wherein an interface structure is automatically analyzed based on an API document, and a basic test case set is generated; flow capturing: monitoring the actual calling condition of the API in real time, and recording the specific content of each request and the corresponding response data; carrying out flow playback: carrying out playback test based on the captured historical flow, and verifying the compatibility of the API; assertion verification: assertion judgment is performed on indexes of the return value and the response time through an assertion mechanism, and abnormity is found; and test report generation: aggregating test result data, generating a test report containing success rate, response time and error log detailed information, and supporting HTML / PDF / JSON export.

The invention belongs to the technical field of table recognition, and discloses a table recognition method, system, medium and equipment based on a multi-modal large model, and the method comprises the following steps: extracting a cell coordinate matrix of a table, and generating a coordinate feature map; establishing a multi-modal large model, and combining the table image and the coordinate feature map to carry out image coding feature splicing to obtain an image feature vector; according to the multi-modal large model, combining the cell coordinate matrix with a set cue word to carry out text coding feature splicing to obtain a text feature vector; fusing the text feature vector and the image feature vector to generate a unified semantic vector; and generating a decoding sequence according to the unified semantic vector to obtain the HTML text content of the table. According to the table recognition method, by setting different token word segments and corresponding recognition technologies, the recognition accuracy of the cells is improved.

The invention relates to the technical field of artificial intelligence testing, discloses a method for automatically extracting UI elements of a Web page based on an AI large model, realizes automatic extraction of positioning information of the UI elements of the Web page of an embedded product, directly provides the positioning information to a Web testing framework for use, and solves the problems of low UI element extraction efficiency and insufficient adaptability in a traditional scheme. Playwright is used for obtaining page screenshots and HTML DOM information, after intelligent cleaning, the page screenshots and the HTML DOM information are transmitted to an AI model to analyze page structures, interactive elements such as buttons and input boxes are automatically recognized, and an optimal selector is generated; furthermore, page navigation and multi-page element collection are realized by combining an AI-driven automatic tool, and finally, an operation sequence is organized through a GUI (Graphical User Interface), so that automatic testing is quickly completed. According to the method, the problems of low efficiency and poor adaptability of a traditional method are solved, the accuracy and maintenance efficiency of Web testing are remarkably improved, and the method is suitable for dynamic and complex modern Web pages.

A computer program product and method include operations including accessing HTML code from one or more webpages, tokenizing the HTML code to form one or more HTML tokens, submitting each HTML token to a large language model, and obtaining a token content description for each HTML token from the large language model. The operations further include determining, for each of the one or more webpages, whether to rendered the HTML code on the web browser based on the token content descriptions of the HTML tokens formed for the HTML code from the one or more webpages.

The invention discloses a DOM-based element identification method and device, and the method comprises the steps: S1, filtering an obtained webpage original HTML according to a set rule to obtain a simplified HTML, and constructing a preliminary DOM tree according to the simplified HTML; s2, performing element type conversion, information fusion and icon information interpretation on webpage elements in the preliminary DOM tree to obtain an extracted DOM tree; and S3, inputting the extracted DOM tree as a part of cue words into a multi-modal large language model MLLM to obtain recognized elements. On the basis of analyzing an original HTML (Hypertext Markup Language), necessary information is reserved, picture description information is supplemented, data integrity is ensured, the MLLM can better understand a webpage and predict operation through the simplified DOM tree, and the analysis efficiency is improved while the use cost is reduced.

The invention provides a front-end logic execution system based on a canvas flow, and the system comprises an editor end which comprises an item switching module which is used for providing an item menu tree and a visual page; the page building module is used for storing a menu component; the action flow arrangement module is used for connecting the menu components according to the running sequence and configuring execution conditions, preposed actions, delay events and loop events to form a low-code data packet; the running device end comprises a data packet analysis module which is used for loading a low-code data packet and restoring the low-code data packet into JSON (JavaScript Object Notation) configuration; the rendering module is used for converting the JSON configuration into HTML (Hypertext Markup Language) elements and JS (JavaScript) codes and rendering the HTML elements and the JS codes to a browser And the event execution module is used for executing each action after the browser component is triggered. The method has the beneficial effects that the generation convenience of the business logic execution link can be improved, the technical threshold of front-end business logic development is reduced, and the flow visualization of the whole link generation and execution links is realized.

The invention relates to a method and equipment for constructing a minority language image-text data set for internet data and a medium, and the method comprises the steps: obtaining an HTML webpage file, extracting a multi-modal document containing minority language image-text data from the HTML webpage file, and screening out image-text related pairs according to replaceable texts corresponding to images in the multi-modal document; inputting a pure picture which does not contain a replaceable text in the multi-modal document, the text information after the picture is removed and a self-defined cue word into a first multi-modal large model, generating corresponding picture description information and image-text question and answer information, forming an image-text description pair by the pure picture and the picture description information, and displaying the image-text description pair in the first multi-modal large model; forming a visual question-answer pair by the pure picture and the image-text question-answer information; inputting the multi-modal document, the image-text related pair, the image-text description pair and the visual question-answer pair into a second multi-modal large model, and outputting an image scene label; and combining the information to obtain a small language image-text data set. Compared with the prior art, the method has the advantages that high-quality, diversified and standardized small language image-text data set construction can be realized.

The invention relates to an intelligent visual crawler configuration system and method based on a large model, and the system comprises a data input module, an AI feature analysis module, a rule generation module, and a visual configuration module, the data input module is responsible for receiving a target website or webpage content, and obtaining an HTML source code or a dynamically rendered complete webpage structure; the AI feature analysis module is used for automatically analyzing structural features and semantic features of a webpage by utilizing a pre-trained AI large model; the rule generation module is used for automatically generating a crawling rule based on an analysis result, wherein the crawling rule comprises a page turning path, list area positioning and field extraction logic; and the visual configuration module is used for providing a visual user interface, displaying an analysis result and allowing a user to manually adjust the generated rule. The problems that an existing web crawler technology is low in efficiency and poor in adaptability in the aspect of webpage rule configuration are solved, the rule generation efficiency is remarkably improved through the system and method, the system and method are suitable for more unknown types of webpages, and the dynamic adaptation and continuous optimization capacity is achieved.

The invention relates to a document writing method and system based on convenient writing and rich interactive rendering, and the method comprises the steps: defining a label grammar, specifically defining a label name, a type, an attribute and a behavior; according to the label grammar, realizing HTML template generation logic corresponding to the label; converting the document content into structured data through a document analysis algorithm; and traversing the structured data, calling HTML template generation logic, and executing view rendering and interaction logic. The bottom layer renders and processes the document through HTML / JS / CSS, and the problem that traditional document styles and interaction are limited can be solved; specific rendering and interaction effects can be completed by setting tag attributes, and the problem of complex document writing can be solved; the content of the table label is in a CSV data format, data redundancy can be further reduced, and data migration is facilitated; label embedding is supported in the CSV format data, and table cell level style control and combination control can be achieved; the invention belongs to the technical field of document writing and can be used for taking notes, writing academic papers and the like.