1733results about "Web data retrieval using information identifiers" patented technology

The invention provides a polyester fabric production whole process monitoring management method and system. The method belongs to the technical field of production process monitoring. The method comprises the following steps: deploying various types of sensors at each key node of a polyester fabric production line; various physical parameters and environment information related to polyester fabric production are collected in real time; meanwhile, an operation state monitoring system of the production equipment is integrated to obtain equipment data; carrying out deep fusion processing on multi-source heterogeneous data obtained from the polyester fabric production holographic sensing architecture; constructing a data association model; comprehensively evaluating the production situation based on the model in combination with the technological process and the quality standard of polyester fabric production; generating a production situation assessment report through production situation assessment; the whole-process data tracing system provides a traceable basis for quality disputes, raw material problems and the like, enhances the capability of controlling supply chain risks, meets the requirements of downstream customers on product traceability, and improves the brand credibility.

The browser tab page data storage method supporting data encryption comprises the steps that browser tab page interaction behaviors are monitored in real time to generate a dynamic factor, and a session key dynamically changing along with the life cycle of a tab page is generated in combination with a process ID of the tab page; based on a self-adaptive encryption strategy, respectively encrypting structured data and unstructured data of the label page; wherein the structured data are encrypted according to field sensitivity levels, and the unstructured data are encrypted through mapping binding of a secret key and the data; the encrypted data and a timestamp voucher of the session key are stored in an associated mode, decryption operation is only allowed to be completed in a label page process memory generating the session key, and the session key is not stored in a landing mode; and when the label page is closed, synchronously clearing the decryption data in the session key and the process memory. According to the method and the device, the defects that the dynamic generation of the key cannot be realized and the key cannot fall to the ground at present are overcome.

A method for overcoming intermittent, temporary, or other fetching failures by using multiple attempts for retrieving a content from a web server to a client device is disclosed. The URL fetching may use direct or non-direct fetching schemes, or a combination thereof. The non-direct fetching method may use intermediate devices, such as proxy server, Data-Center proxy server, tunnel devices, or any combination thereof. Upon sensing a failure of a fetching action, the action is repeated using the same or different parameters or attributes, such as by using different intermediate devices, selected based on different parameters or attributes, such as different countries. The repetitions are limited to a pre-defined maximum number or attempts. The fetching attempts may be performed by the client device, by an intermediate device in a non-direct fetching scheme, or a combination thereof. Various fetching schemes may be used sequentially until the content is retrieved.

A method for overcoming intermittent, temporary, or other fetching failures by using multiple attempts for retrieving a content from a web server to a client device is disclosed. The URL fetching may use direct or non-direct fetching schemes, or a combination thereof. The non-direct fetching method may use intermediate devices, such as proxy server, Data-Center proxy server, tunnel devices, or any combination thereof. Upon sensing a failure of a fetching action, the action is repeated using the same or different parameters or attributes, such as by using different intermediate devices, selected based on different parameters or attributes, such as different countries. The repetitions are limited to a pre-defined maximum number or attempts. The fetching attempts may be performed by the client device, by an intermediate device in a non-direct fetching scheme, or a combination thereof. Various fetching schemes may be used sequentially until the content is retrieved.

The invention discloses a webpage data collection method and a related device, and relates to the technical field of data processing.The webpage data collection method comprises the steps that a webpage data collection knowledge base containing data collection modes of various webpages is constructed in advance; a data acquisition mode matched with the webpage is obtained from a webpage data acquisition knowledge base, and the data acquisition mode defines that an analysis mode of each field in the webpage is analyzed based on multi-modal features (at least two of DOM structure fingerprint features, visual position features and semantic features of the fields); according to the method, the analysis accuracy of the webpage data can be greatly improved, so that stable and efficient execution of a webpage data acquisition task is guaranteed.

Techniques for URL handling in Retrieval-Augmented Generation (RAG) systems are disclosed. A RAG system uses a generative AI response in the selection of links to include in a modified output from a RAG system. The links are based on URLs that are extracted from ingested documents. In response to a query, the system generates a response and then performs a matching operation to match a portion of the generated response to a URL in a URL-keyword mapping. The system finds a match between a portion of the generated response and a keyword that is associated with a URL, generates a hyperlink using the matched URL, and adds the hyperlink to the response.

The invention discloses a data tamper-proofing method, system and device based on blockchain evidence storage, and a storage medium, relates to the field of data processing, and is used for solving the problems that multi-source heterogeneous data lacks a unified processing scheme and evidence storage verification is incomplete in existing property management. The method specifically comprises the following steps: multi-modal feature processing: extracting text and image data features respectively, and generating a unified feature vector by combining cross-modal attention mechanism weighted fusion; generating a hash value and a block chain evidence, generating the hash value by adopting an SHA-256 function, and generating a dynamic two-dimensional code in an association manner; and user verification: after scanning the two-dimensional code, locally reproducing feature processing and Hash calculation, and comparing a Hash value on a chain through an elliptic curve cryptography technology to complete verification. According to the method, full-process credible evidence storage of the property data is realized, the data tamper-proofing capability and verification convenience are improved, and property scene data management requirements are met.

The invention relates to the technical field of block chain food traceability, and discloses a block chain-based food traceability method and system, and the method comprises the steps: carrying out the timestamp processing of a batch number, a production date, a transportation temperature and storage humidity, and calculating a dynamic guarantee period to generate a traceability record; encrypting the batch number and the dynamic shelf life to generate a tamper-proof hash value; when the temperature and the humidity exceed threshold values, food state records are generated in combination with the Hash values; synchronizing the food state record to a supply chain node and performing consistency verification to obtain a shared data set; generating a credible two-dimensional code containing a batch number, a dynamic shelf life and a circulation record based on the shared data set; the consumer executes verification after scanning the code, extracts the shelf life field and the circulation information abstract, and compares the dynamic shelf life with the current time to generate a user interface; and consumer feedback is extracted, batch matching is verified through a timestamp, and a food traceability report is generated. The food state can be reflected in real time, data tampering is prevented, and traceability credibility is improved.

The invention discloses an automatic generation method for health science popularization articles, and belongs to the crossing field of computer technology and health science popularization. The method comprises the following steps that S1, health authority information is collected through a multi-source crawler, and an original material pool is obtained through Sension-BERT vectorization duplicate removal and BioBERT medical entity labeling; s2, classifying nine types of health themes by using a RoBERTa fine tuning model; s3, multiple AI model supplementary materials are made into a structured package; s4, predetermining optimal selection questions in combination with AI three-dimensional scoring and editing; s5, calling the multi-dimensional knowledge base to generate a professional knowledge packet; s6, generating an outline and performing three-dimensional five-score system auditing of knowledge point fullness and the like; s7, the LLM expands and writes the text and marks knowledge sources; s8, performing double-stage auditing; s9, anthropomorphic draft moistening; s10, intelligently illustrating the picture; s11, when the matching degree is smaller than a preset threshold value, automatically updating the knowledge base; and S12, integrating and outputting. According to the method, the health science popularization article is generated, the manual participation time is shortened to be within 30 minutes, the medical error rate is reduced to be below 5%, the daily output of a 10-person team is improved by 3-5 times, the annual human cost is reduced by 60% or above, and the large-scale and high-quality science popularization requirements are met.

In a threat management platform, a number of endpoints log events in an event data recorder. A local agent filters this data and feeds a filtered data stream to a central threat management facility. The central threat management facility can locally or globally tune filtering by local agents based on the current data stream, and can query local event data recorders for additional information where necessary or helpful in threat detection or forensic analysis. The central threat management facility also stores and deploys a number of security tools such as a web-based user interface supported by machine learning models to identify potential threats requiring human intervention and other models to provide human-readable context for evaluating potential threats.

A method for automatically inserting hyperlinks is provided. In one example, the method includes determining a location for a hyperlink anchor in a document based on a type of structural element identified in the document. A presentation of the hyperlink anchor may be displayed according to a set of rules defining an appearance of the hyperlink anchor according to the type of structural element.

A computer-implemented method is disclosed for controlling the disclosure (e.g., flow) of sensitive information from a document in a computer application running on a computer endpoint device to a tool (e.g., a generative artificial intelligence tool) hosted at a remote network destination. The application is configured to selectively enable or disable in-line access to the remote generative artificial intelligence tool from within the document. The method includes receiving a notification (e.g., at a computer-implemented endpoint agent) that a document has been opened in the application, obtaining text from the open document, determining (e.g., with a computer-implemented scanning engine) whether the text from the open document contains sensitive information based, at least in part, on content of the text, and disabling the in-line access to the generative artificial intelligence tool at the application in response to determining that the content of the text from the open document contains sensitive information.

Embodiments include an activity monitoring machine learning model method. One embodiment the method includes transforming HTTP network requests into feature vectors, each feature vector representing selected features from a corresponding HTTP network request and an action selected from a plurality of actions to be monitored and inputting the feature vectors into a machine learning model to train the machine learning model to classify new HTTP requests according to the plurality of actions, wherein the plurality of actions include an upload action and a download action.

A method for providing secure access to cloud computing resources comprising: monitoring communications in sessions between a cloud computing resource, CCaaS, of cloud computing resources and users using web browsers comprised in user equipment, UE, to access the CCaaS; processing the monitored communications to accumulate data for at least one component or any combination of more than one of a set, CCaaS-KPI, of key performance indicators, KPIs, that characterize operation of the CCaaS during the sessions, a set, UE-KPI, of key performance indicators characterizing operation of the user equipment, UE, during the sessions, a set, U-KPI, characterizing actions of users accessing the CCaaS during the sessions, and / or a set, SMETA, of session metadata components that provide indexing and descriptive data for the sessions; processing the accumulated data to determine patterns characterizing normal interaction of users with the CCaaS; and using the normal patterns to detect an anomaly in a user session in which the user engages with the CCaaS.

A system and method for verifying the authenticity of information associated with an entity and communicating the verification status of the information across a network. The system facilitates the receipt of data relating to information associated with an entity so that a corresponding data record can be created and stored in memory. A visually perceptible element, which corresponds to the verification status of the data record, is associated with the data record so that the visually perceptible element can be displayed to a requesting computing device to communicate the verification status of the data record. If the verification status of the data record is changed, the visually perceptible element associated with the data record is changed to reflect the new verification status which is automatically changed for any requesting computing devices so that the new verification status is communicated to the public from any platform displaying the visually perceptible element.

The invention discloses an intelligent business handling process management and control platform, and particularly relates to the technical field of computers, the management and control platform is internally provided with a dynamic process engine module, and the dynamic process engine module is used for analyzing a third-party platform business process structure, supporting visual configuration of process nodes and rules and realizing automatic execution and scheduling of a process. And the flow execution process is monitored and fed back. According to the method, through automatic analysis and adaptation of dynamic changes of the third-party platform, reinforcement learning of dynamic scheduling resources, full-link monitoring and intelligent diagnosis, the problems of high adaptation cost, low resource scheduling efficiency and insufficient monitoring capability in traditional process management and control are systematically solved, and the automation rate, execution efficiency and stability of the business handling process are comprehensively improved.

An automated system attempts to characterize code as safe or unsafe. For intermediate code samples not placed with sufficient confidence in either category, human-readable analysis is automatically generated to assist a human reviewer in reaching a final disposition. For example, a random forest over human-interpretable features may be created and used to identify suspicious features in a manner that is understandable to, and actionable by, a human reviewer. Similarly, a k-nearest neighbor algorithm may be used to identify similar samples of known safe and unsafe code based on a model for, e.g., a file path, a URL, an executable, and so forth. Similar code may then be displayed (with other information) to a user for evaluation in a user interface. This comparative information can improve the speed and accuracy of human interventions by providing richer context for human review of potential threats.

The present invention generally relates to systems and methods for the efficient and secure creation of unique identifier associated with submitted URLs and the transmission and processing of encrypted signals by a receiving device, and in particular an audio transmission and processing of encrypted unique inaudible signals by a receiving device that may direct the receiving device to initiate an action, such as directing the receiving device to request an associated Uniform Resource Locator (URL) to then access a specific URL or other digital content through a browser application. The decoding and processing of the transmitted signal is operated on prior to the signal being played through the receiving devices speaker system(s). Consideration of the available signal bit rate is another aspect of the system's operational integrity.

Systems and methods are disclosed herein for identifying accessibility issues in web sites and for remediating website accessibility issues to thereby facilitate website navigation by people with diverse abilities.

The invention discloses a processing method and device for search engine optimization, electronic equipment and a storage medium, and the method comprises the steps: carrying out search optimization for obtaining search engine recommendation on a target information object to be put into a network through a target generative model, and obtaining an optimized target information object; putting the optimized target information object to a network; searching metadata by an engine for searching the optimized target information object, and accessing the metadata by a user; generating multi-dimensional model optimization data according to information content, engine search metadata and user access metadata contained in an optimized target information object page released to a network, and a search-recommendation rule of a search engine; optimizing and storing the target generative model by adopting an optimization mode matched with the model optimization data of each dimension; therefore, the ranking of the website links of the optimized target information object in the search result of the search engine is improved.

The invention provides a UI automatic test system and method, computer equipment and a storage medium, a manual case structuring module receives a manual case and converts the manual case into structured data in a preset format; the page element obtaining module calls a browser driving engine according to the target URL to obtain full page elements; the AI element matching module is used for scoring full elements of a page through a pre-matching algorithm based on operation types and interface element descriptions in the structured data, screening out first K elements, and carrying out secondary screening through a large model to determine target elements; and the automatic use case execution module generates an automatic test use case according to the target element and the operation data in the structured data, executes the automatic test use case and verifies whether an execution result conforms to expectation or not to realize UI automatic testing. By the adoption of the scheme, the labor cost of UI testing is reduced, the efficiency and adaptability of UI testing are improved, and then the automation level and the large-scale capacity of UI testing are improved.

Systems and methods include receiving a customer domain from a user via a user device; parsing a plurality of candidate look-alike domains based on the customer domain; executing at least one detection technique selected from a plurality of short URL detection techniques to determine whether one or more short URLs redirect to one of the plurality of candidate look-alike domains; and in response to determining, by the at least one detection technique, that the one or more short URLs redirect to one of the plurality of candidate look-alike domains, classifying that candidate look-alike domain as a phishing attempt.

The invention belongs to the technical field of data processing, and particularly discloses a multi-source heterogeneous data acquisition access method and system based on intelligent mapping and a dynamic interface, and the method comprises the steps: registering an input data source class, generating a data source identifier corresponding to the data type, and storing the data source identifier; respectively executing meta-model analysis operation to generate a standardized meta-model associated with the data source identifier and a container instance template; generating a mapping rule set through a twin neural network architecture with multi-modal feature fusion and a preset mapping rule; a middle layer API interface is constructed through interface logic, and real-time conversion and access between input and output data are achieved; and realizing containerized parallel access based on the container instance template and the containerized interface service instance. According to the method, data source change is dynamically adapted, the real-time performance and accuracy of the mapping rule are ensured, and meanwhile, multi-source heterogeneous data can be accessed efficiently in real time in combination with containerized parallel processing and a data source change monitoring mechanism.

Provided is a system and method for digital content generation and recommendation. A first plurality of stories are collected from various content sources over a network. A second plurality of stories are selected from the first plurality of stories such that a degree of similarity between any two stories of the second plurality of stories is below a determined threshold. A summary and a headline are generated for a first story of the second plurality of stories. A set of images are selected, from an image database, for the first story based on the generated summary and headline. A multimedia item including the summary, the headline, and a first image of the set of images is created. The multimedia item is presented on a lock screen interface of a user device, displaying the generated summary, the generated headline, and the first image on the lock screen interface.

The invention relates to the field of internet search service, and discloses a big data-based investment attraction clue analysis system, which comprises a query analysis unit, a query analysis unit, a query analysis unit, a query analysis unit and a query analysis unit, wherein the query analysis unit calls an event sequence template for defining a meta event type and a standard relative time window constraint interval; the distributed retrieval and aggregation unit is used for retrieving and aggregating meta event types to entity objects; the sequential logic verification unit is used for counting the global document frequency of the meta event, reversely mapping the global document frequency to generate a zoom coefficient, dynamically correcting a time window, and judging that only an entity object in a dynamic verification interval after correction is passed; the object sorting unit generates sorting scores according to template matching integrity, and by constructing a density and window reverse coupling mechanism, the sequential logic boundary is adaptively compressed in a high background noise environment, and the retrieval signal-to-noise ratio and the logic confidence coefficient are maintained.

The invention provides an open source compliance efficient scanning method and system oriented to an operating system, and belongs to the technical field of information. Open source compliance scanning is divided into a plurality of scanning items, and configurable differential scanning is achieved; after the scanning task is triggered, judging a main task type, acquiring a scanning object according to the main task type, and reading a scanning template corresponding to the main task type; extracting metadata information of the scanned object, and generating a uniform resource locator (PURL); a distributed task scheduling framework is adopted, subtasks are created for scanning items, distributed subtask distribution is carried out based on execution cost calculation, and scheduling and execution of the subtasks are managed. According to the method, strict requirements on open source compliance in the development and maintenance process of the operating system and the management process of the supply chain are met.

The invention provides a Web page first screen loading acceleration method and system, a medium and equipment, and relates to the technical field of Web front-end performance optimization and network transmission, the method comprises the following steps: after obtaining a request of a user for accessing a URL (Uniform Resource Locator), analyzing an HTML (Hypertext Markup Language) and constructing a DOM (Document Object Model) tree; marking first screen resources to obtain a first screen resource list; key resources are inserted into the head of the loading queue, and non-key resources are marked as defer; if the weak network is detected, degrading the picture quality; after the CSSOM is ready, text and layout are rendered immediately, and placeholders are replaced after pictures are asynchronously loaded; when the delay is high, switching to an edge CDN node or starting a QUIC protocol; and pre-fetching resources are predicted based on user behaviors, and the pre-fetching resources are stored in a Service Worker cache. According to the method, the first screen loading time can be shortened, the maximum content drawing time is shortened, the network transmission cost is saved, and the cache utilization efficiency is improved.

The invention relates to the technical field of automatic office, in particular to a paper form data intelligent identification and storage method and system, and the method comprises the following steps: obtaining a paper form image through an image collection device; preprocessing the form image; identifying each data item in the form image through a multi-model fusion OCR identification framework, performing intelligent error correction based on industry knowledge and semantic modeling after identification, constructing a structured mapping model by using the identified content, and associating the model with a two-dimensional code on the form to form a form identification template; a specific recognition template is called through code scanning, a database to which form data belongs is directly determined according to the template and the form data according to geometric positions, table names and field names in the database are created according to semantic tags of data items, intelligent rapid storage of recognition results is achieved, and position coordinates of the data in the form are continuously corrected by adopting a sliding positioning mechanism. The method has self-learning optimization capability, can adapt to severe working environments, can realize continuous upgrading and new scene expansion, and has practical value and popularization prospect.

A method for suggesting prompts on a page of a workspace includes receiving an input and displaying a prompt block configured to initiate a generative process to create in-block content in response to the input. The prompt block is embedded as an in-page object on the page. The method includes causing a large language model (LLM) system to create a set of suggested prompts. Each prompt includes instructions configured to create generative content of a respective type by the LLM system. The set of suggested prompts is created based on in-page text content or a relative location of the prompt block on the page. The method includes displaying the set of suggested prompts as a set of control items of the workspace. Each of the set of control items is selectable to input as a prompt for generating content based on existing content of the workspace.

The invention provides a social listening data noise reduction method and device based on a large language model, and belongs to the technical field of social media data processing. The method comprises the steps that social media data are collected and preliminarily filtered to obtain preliminarily filtered data; generating a semantic embedding vector by using a pre-trained large language model, and screening semantic related data in combination with cosine similarity and context; identifying and filtering duplicate and variant contents through an embedded model and a generative adversarial network to obtain duplicate-removed data; performing multi-modal feature extraction on the de-duplicated data, and screening credible data in combination with generative AI detection and sentiment analysis; and filtering semantic inconsistency and non-topic continuation texts by adopting a clustering algorithm and semantic relationship analysis to finish noise reduction. According to the method, through a multi-stage and multi-dimensional noise reduction strategy, the purity and credibility of social listening data are effectively improved, and high-quality data support is provided for subsequent topic analysis and decision making.