1576 results about "Web site" patented technology

A system and method is described for internationalization of web pages by extracting translatable content from extensible mark-up language (XML), or similar data-centric meta-language representations of web pages or data used to build web pages. The extracted translatable content is stored in a translation task repository (TTR) accessible by the web developer and the translator. The XML representation is then modified to include selection control logic to select the appropriate translations for insertion into the final web page. The translator accesses the TTR to translate the appropriate content and saves the translations back to the TTR associated with the original translatable data. The translations are obtained from the TTR as selection cases for the selection control logic of the XML representation. As the XML is converted into the web source code, the selection logic and translations are embedded therein facilitating building the web site in multiple different languages.

The method and systems for automatically identified currently viewing website domain name or a uniform resource locator (URL), receiving, by the server, said automatically identified website domain name or the uniform resource locator (URL), a request or an invitation for initiating a communication including live chat, puts the request for initiating a communication including live chat from the first user and the second user in a communication including live chat queue of the website or the uniform resource locator (URL) associated account, for available or identified or relevant agents to pick up, routing request or invitation for initiating a communication including live chat from the first user and the second user according to a pre-set rules and start a communication including live chat by available agent by selecting particular request for initiating a communication including live chat from the queued communication including live chats.

A platform for dynamically generating application experiences. The platform comprises a design management system, an agent orchestration system, an analytics system, a model management system, a user management system, and databases for storing design elements and templates. The design management system provides a portal for application owners / designers to create UX / UI designs, allowing them to select design elements from a set of categories or templates. The platform gathers existing websites / applications to identify common design patterns, stored in a design catalogue database, and suggests historical interfaces for design exploration. It enables the generation of templated applications that integrate with legacy systems. The agent orchestration system parses user specifications, selects generative AI systems, and generates UX / UI content based on the specifications. The analytics system collects and analyzes data to provide insights for improving UX / UI design and optimizing website performance. The model management system trains and maintains generative AI models used for content generation.

The present invention relates to a system for transforming static websites into artificial intelligence (AI)-enabled interactive multi-modal conversational platforms. The system comprises a computing device having a processor for receiving user queries as text or speech input through an input module cooperating with a speech-to-text module. A natural language processing (NLP) module interprets intent, classifies user context, and retrieves grounded information from multiple webpages. A persona adaptation module dynamically modifies vocabulary, tone, and avatar representation across roles such as sales assistant, recruiter, educator, healthcare professional, etc. A response generator module produces structured natural language output, transmitted to a text-to-speech synthesis module and an avatar generation module to render synchronized lifelike video responses. An output rendering module displays multi-modal responses include text, audio, and video, thereby enabling direct navigation and escalation beyond limitations of conventional static websites.

The invention provides a data analysis mapping method and system based on context awareness, and the method comprises the steps: carrying out the directional crawling of a target website through a crawler instance, so as to obtain multi-format webpage source data, then extracting the structural features, semantic features and source features of the multi-format webpage source data, and constructing a source data context feature set; dynamically matching an adaptive analysis strategy based on the source data context feature set to accurately extract target field data, performing semantic similarity matching on the target field data and a preset service scene standard field library, and performing data format unified conversion in combination with a context format rule to obtain standardized field data; and finally, performing multi-dimensional verification on the standardized field data, and generating an SQL statement after the verification is passed, so as to solve the problems that an existing data analysis mapping scheme depends on a fixed template and cannot dynamically adapt to page structure change of a target website, manual auxiliary field mapping consumes time, and errors are easy to introduce.

The present technology relates to a computer-implemented method for enhancing enterprise-wide security when using Artificial intelligence (AI) models. Embodiments involve a JavaScript injection process facilitated by a proxy server. This process does not require manual installation as it is automatically injected during operation. The JavaScript injection process operates by intercepting unsecured AI input and output data provided by users interacting with AI websites. The input and output data are sent to a security Application Programming Interface (API) which applies an enterprise security policy to the data in real-time, thereby transforming unsecured input and output into secure data. Embodiments provide a robust framework for safe interaction with Artificial intelligence models while mitigating the risks associated with the transmission of sensitive information over the internet.

A modular system designed for privacy-preserving content recognition and supplemental content delivery across web and mobile environments. The system employs lightweight character sampling and vision-based recognition to generate unique content fingerprints without storing or replicating original data. It features a hybrid processing architecture, using local computing resources for intensive tasks while optimizing performance on resource-constrained devices. Core functionalities include multi-method content fingerprinting, real-time monitoring with adaptive sampling, and secure supplemental content association. Operating entirely on the client-side, it complies with website terms of service and privacy regulations. Advanced features include AI-driven content recognition, blockchain-based verification, and granular content targeting through resizable selection interfaces. This technology enables seamless delivery of supplemental content while preserving privacy, reducing resource usage, and ensuring scalability across browsers, mobile applications, and edge devices. It is particularly applicable in industries such as education, retail, and secure data sharing.

The present application discloses a method, system, and computer system for providing real-time detection of malicious URLs based on a machine-learning powered domain risk scoring. The method includes (i) identifying a subset of higher risk websites, wherein the higher risk websites are at risk for potential malware injection or modification, and (ii) in response to identifying the subset of higher risk websites, performing an active measure based at least in part on the identified subset of higher risk websites.

The invention provides a data verification method based on two-dimensional code third-party login and national secret authentication, and the method comprises the steps: obtaining a user identity bill and obtaining a private key password corresponding to the user identity bill by an encryption end when a login request sent by a user end through scanning a login two-dimensional code of a login end is received; the encryption end encrypts the private key password to obtain an encrypted key password, and sends the encrypted key password to the login end; the encryption end determines collaborative signature response data according to the collaborative signature request and the user identity bill and sends the collaborative signature response data to the login end; and the encryption end verifies the complete signature through the verification request, and sends a verification result to the authentication end. By arranging the encryption end, national secret authentication and two-dimensional code third-party login are combined, and the safety of logging in a third-party website when the two-dimensional code is scanned is guaranteed.

A method and a system for building a knowledge base for industrial use and using the knowledge base to manage and control industrial products, processes, resources and systems. The knowledge base uses semantic processing modules and artificial intelligence tools to enable continuous extraction and entry of knowledge into the knowledge base from various sources including user inputs, operation status reports, manuals, websites, diagnosis reports, sensor data, operation sequence, and other static or ephemeral sources. The knowledge base is supported by a knowledge base management system that includes a suite of tools to support knowledge entry, update, retrieval and visualization using both natural language based queries and structured queries with predefined syntax. The system also provides tools to retrieve and assemble knowledges on-the-fly to support industrial applications including to design products, services or production lines, build production process, manage scheduling and flow, monitor and optimize operations, diagnose issues, apply business logics, procure materials and supplies, manage and train workforce, and provide customer supports.

A method and system for limiting mobile device functionality when the mobile device is located in a pre-defined fixed geographic area. The mobile device may receive a local disabling signal from a disabling device, which, when detected by a Device Owner Application resident on the mobile device, limits the mobile device functionality. Alternatively, the system may use GPS based geofencing to determine that the mobile device is in a predefined geographic area, and then transmit instructions to the mobile device, where a Device Owner Application operates to restrict the mobile device functionality. Mobile device functionality may be limited by restricting the mobile device's ability to send and receive text messages, email messages and phone calls; restricting the mobile device's ability to respond to user input; restricting the mobile device's ability to utilize a web browser; and restricting the mobile device's web browser from accessing predetermined web sites.

The invention designs a cross-Tor version domain small sample website fingerprint identification method based on comparative learning. The method comprises three parts of a pre-training strategy based on comparative learning, a fine tuning strategy based on double-branch confidence alignment and a flow classification strategy driven by a prototype. The method comprises the following steps: firstly, constructing a discriminative representation space through a trunk convolution feature extractor and a traffic attention module based on a pre-training strategy of comparative learning, and introducing supervised comparative learning to obtain feature representation with a cross-domain migration capability; secondly, a double-branch confidence alignment fine tuning strategy is adopted, the stability of a model structure is kept in combination with a partial freezing mechanism, and rapid adaptation to a target domain is achieved through joint optimization of cross entropy loss and weighted comparison loss; and finally, introducing a prototype-driven classification strategy, and on the basis of a semantic structure formed in a fine tuning stage, realizing accurate identification of Tor traffic in closed world and open world scenes by using a category prototype, so that the cross-domain generalization ability of small sample website fingerprint identification is remarkably improved.

The invention relates to a user portrait recognition method and a website recommendation method based on semantic analysis, and the user portrait recognition method comprises the steps: dividing a website which is browsed by a current user in a first preset time period and relates to the same category into a plurality of sub-categories, and taking each sub-category as a point of a portrait; and for each sub-category, determining the sub-category as a current sub-category, determining other sub-categories as adjacent sub-categories, constructing edges, pointing to all the adjacent sub-categories, of the current sub-category, and taking a correlation coefficient, pointing to the adjacent sub-categories, of the current sub-category as a weight of the edges to form a user portrait. Consumption habits of consumers and relevance among different commodities are fully considered, on the basis, recommendation weights of websites are corrected layer by layer through browsing information and consumption information of current users in combination with browsing information and consumption information of group users, personalized and high-accuracy website recommendation schemes are provided for the users, and user experience is improved. And the user experience is improved.

The invention relates to the field of data analysis and cleaning, in particular to a method and system for automatically collecting and cleaning public opinion experimental data. The method comprises the following steps of performing periodic data crawling on a public information website, performing public opinion hotspot analysis, and extracting a to-be-processed hotspot event stream; performing keyword detection and global content distribution analysis on the to-be-processed hot event stream to obtain a keyword frequency distribution diagram; performing negative emotion deep recognition according to the to-be-processed hot event stream, and extracting negative emotion public opinion data; performing negative public opinion evolution trend prediction based on the keyword frequency distribution diagram to obtain a negative public opinion propagation situation; and performing IP address tracing on the negative emotion public opinion data to obtain the negative public opinion region sensitivity. According to the method, comprehensive and accurate abnormal public opinion detection and deletion are realized, and the network information quality and the public governance level are improved.

The disclosed computer-implemented method may include generating an interface code configured to connect to a payment server and generating, in response to loading a merchant website hosted on a merchant server that integrates the interface code, a payment interface with the interface code. The interface code may bypass the merchant server to connect to the payment server. The method may also include completing a payment using the payment interface that bypasses the merchant server to connect to the payment server. Various other methods, systems, and computer-readable media are also disclosed.

The invention relates to the field of network security and the deep learning field, in particular to a satellite internet-oriented Tor website fingerprint identification method, which is implemented by constructing a self-supervised contrast learning framework and is implemented by generating a multi-view sample; extracting a feature matrix of the time sequence granularity; generating a synthesized negative sample based on linear insertion, and constructing a contrast with the positive sample; and track representation is extracted, and joint optimization is carried out in combination with cross entropy loss and mask reconstruction loss. Compared with a traditional website fingerprint identification method, the robustness of the model to satellite inherent noise caused by the Doppler effect can be enhanced. According to the method, multi-scale semantic features are provided for the weak enhancement view and the strong enhancement view, the inter-class distinction degree is improved by synthesizing negative samples, and the misjudgment rate is reduced; the joint loss optimization framework enables the model to give consideration to global statistical characteristics and local burst characteristics, and under the conditions of strong dynamic topology and limited labeling of satellite internet constellations, the accuracy and adaptability of website fingerprint recognition are remarkably improved.

The invention relates to the technical field of artificial intelligence, in particular to a multi-modal large model-based bidding and cross-bidding early warning and blocking method and system, and the method comprises the following steps: receiving and preprocessing various qualification files, including business licenses, industry licenses, auditing reports and bidding files, submitted by suppliers; applying a document layout analysis model based on joint training of a visual coding network and a text alignment network; the method has the beneficial effects that a scanned certificate, an audit report and a bidding file are automatically analyzed into structured semantic fragments; performing same semantic space alignment on the fragments, supplier basic information, historical records and real-time captured data of an authoritative authentication website; any contradiction or gap among different sources of key information such as registration capital, permission items, financial indexes and the like can be quickly found, and interpretable risk scores and processing suggestions can be given; on the premise of ensuring the private security of the data, the qualification auditing efficiency and accuracy are improved, and the workload of manual checking is reduced.

The invention provides a self-adaptive transformation and migration method and system for an internal website, and relates to the technical field of website migration. Comprising the following steps: constructing a hierarchical credential adaptation architecture, establishing a dynamic authority-data mapping mechanism, realizing knowledge base-data migration linkage and deploying an adaptive security protection chain. The method is used for realizing collaborative improvement of compatibility, security and knowledge service efficiency of an internal website in a credential environment through hierarchical credential adaptation, dynamic permission and data association, knowledge base linkage and self-adaptive security protection; besides, through cooperative work of the hardware driving adaptation module and the software interface conversion module, automatic identification of hardware features and interface features, precise analysis of adaptation requirements and dynamic generation of configuration files are realized. The compatibility of an internal website to different models of servers, autonomous controllable components and software interfaces in a credential environment is remarkably improved, the adaptation period is shortened, and stable operation of the system is guaranteed.

The invention discloses a website testing method and device based on multiple agents and a medium, and relates to the technical field of computers, the method comprises the steps of receiving a testing task, analyzing the testing task, determining a testing type contained in the testing task, and dividing the testing task into a plurality of testing subtasks based on the testing type; acquiring a corresponding test capability label, matching the test capability label with the test type, and respectively determining execution agents corresponding to the plurality of test sub-tasks; the test subtasks are concurrently sent to the corresponding execution agents, so that the test subtasks are concurrently executed through the execution agents; receiving test result data returned by the execution agent, and generating structured result data; and constructing a test result visual chart, and sending the test result visual chart to a front-end interface for display. The task is split according to the test type, and the intelligent agent with the corresponding capability is matched for testing, so that the website testing efficiency and the coverage integrity are improved, and the limitation of the traditional single-thread testing is broken through.

Disclosed embodiments provide a framework for provisioning a virtual browser application environment accessible using a native browser application. The virtual browser application environment is implemented on a virtual machine instance, where the virtual environment is isolated from other functionality of the virtual machine instance. In response to a request to access the environment, a set of access control policies are identified. The access control policies define a level of access to actions that can be performed within the environment. The environment is presented through a website executed on a user's native browser application. The user's interactions with the environment and with any other users within the environment are monitored in real-time according to the access control policies.

An example process includes causing a website of a merchant to load to an in-app browser within a payment application executing on a user device of a user. The example process further includes presenting, via a user interface of the user device, an interactive element on a checkout page of the website. A determination is made that the interactive element has been selected. The selection generates a payment request for a payment to the merchant from a user account associated with the payment application. The payment request is received via the in-app browser to initiate payment from the user account. The example process further includes determining that the payment request originated from within the payment application and is associated with a stored balance associated with the user account. The user account is accessed, and the payment is caused to be authorized without additional input from the user.

The present disclosure provides a search engine optimization (SEO) system comprising a remote server. The remote server comprises a memory with a set of executable routines and a search engine database with multiple fields of applications, each associated with multiple URLs indexed with a user engagement matrix, written data, and a search engine ranking. A processor acquires a web link from a computing device, extracts textual content, analyzes relevancy, and retrieves relevant URLs. The processor evaluates a thematic score, a readability score, and an emotional tone data using NLP techniques, analyzes written data of each URL to determine a topic weight, a legibility weight, and a sentiment tone data, develops a machine learning model, applies the model to recommend content alterations, and renders the alterations at the computing device.

The invention relates to the technical field of network advertisement processing, and discloses a method for intelligently identifying and automatically closing website advertisements based on a multi-modal large model. The method comprises the following steps: acquiring text data, image data and interactive behavior data of a website page in real time, and performing format standardization processing on each modal data to obtain a multi-modal original data set; extracting text features, image features and behavior features of the advertisement candidate area according to the data set, and establishing a feature association index; performing cross-modal semantic fusion on the feature association index through a pre-trained multi-modal large model to generate an advertisement recognition probability value; comparing the advertisement recognition probability value with a preset threshold value, judging whether the advertisement candidate area is a target advertisement or not, and generating a recognition result; and triggering a page element operation instruction based on the identification result, executing an automatic closing operation on the target advertisement area, and recording an operation log. According to the method, interference of advertisements on user browsing is effectively reduced, and network use experience is improved.

Accuracy, reliability, and response speed improvements for software applications executed by a computing system or platform are provided herein. There are provided systems and methods for multidimensional error causal analysis for error intercorrelations that impact application availability. A service provider may utilize different computing services for data processing to provide different computing services to users, such as via websites and / or applications of the service provider. Due to errors, users may be unable to utilize applications or may face decreased performance and application availability. To improve application performance, error causal analysis may be performed that identifies error intercorrelations that impact application availability and other performance by identifying error effects on each other. Causal statements may be intelligently generated to then identify error intercorrelations. Once generated, these statements may be tested and verified to allow debugging teams and others to fix errors that reduce application performance and availability.

A system and method for automated domain advertising utilizing artificial intelligence is provided. The system includes a processor and memory in communication with the processor. The memory includes a user interface module, a domain advertising (DA) module, an artificial intelligence (AI) module, a posting module, and a domain parking module. The system receives the domain name from a user. The AI module generates the domain advertising suggestion based on the domain name. The domain advertising suggestion is provided to the user and may be posted to social media or a domain parking website. The AI module includes a large language model (LLM) and a retrieval-augmented generation (RAG) module. The RAG module includes a knowledge base to retrieve a knowledge-based response from an external knowledge source, an expert module to retrieve an expert response from a specialized domain model, and a ranker to rank the knowledge-based response and the expert response.

A system and method for evaluating narrative, entertainment, or message-based content using a multi-axis diagnostic framework. The system processes a media input—such as a screenplay, advertisement, website, short-form video, or branded communication—through modular scoring layers including artistic merit, commercial potential, demographic alignment, genre fidelity, and ideological sensitivity. Optional components include symbolic tagging, AI-origin detection, and cultural volatility indices. The results are compiled into a structured Media Scorecard comprising numerical scores, qualitative diagnostics, quadrant resonance maps, and role-specific summaries. The system may be deployed as desktop software, cloud platform, or API-integrated service, and optionally incorporates machine learning to refine scoring and forecast performance. Outputs are used to inform development, marketing, investment, and acquisition decisions across entertainment and media ecosystems.

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 discloses an intelligent media content association propagation and influence analysis method based on a knowledge graph, and the method comprises the following steps: collecting multi-source media data from social media, a news website, a video platform and a forum, and constructing and forming a heterogeneous knowledge graph; performing feature initialization and embedding on nodes in the heterogeneous knowledge graph to generate initial node embedding representation; constructing a dynamic heterogeneous graph attention network based on the node initial embedding representation to obtain a node dynamic propagation state representation; calculating a propagation influence score based on the node dynamic propagation state representation to obtain a node influence sorting result and a core propagation path; and introducing a causal consistency training mechanism based on the core propagation path, optimizing parameters of the dynamic heterogeneous graph attention network, and outputting a propagation influence evaluation result. According to the method, the dynamic heterogeneous graph attention network is adopted, and intelligent analysis of the media content propagation influence is realized.

The invention discloses a multi-label website fingerprint identification method and system based on attribution analysis, and the method comprises the steps: firstly carrying out the model attribution analysis of a training sample, and constructing an average discrimination template of each website category; high contribution areas of all categories are extracted according to the average discrimination template, and a structured mask template used for guiding identification is formed; in the identification stage, sliding window matching is carried out on input hybrid network traffic, the position of a potential pseudo sub-stream is judged according to the similarity between a mask template and a window sub-sequence, and single-label identification is carried out on the extracted pseudo sub-stream, so that effective analysis of multi-label traffic is realized. The method has the advantages of being high in structure perception, high in template generalization and good in mixed flow adaptability, the website recognition capacity in a complex network environment can be remarkably improved, and the method is suitable for scenes such as encrypted communication monitoring and anonymous channel flow analysis.

The invention discloses a Tor network exit traffic identification system and method fusing a multi-scale LSTM and a Transform network, and belongs to the technical field of anonymous network traffic analysis and network security. The system comprises five core components, namely a multi-scale feature extraction module, a feature fusion module, a global dependency modeling module, a dynamic weighted aggregation module and a classification module. The multi-scale feature extraction module adopts parallel bidirectional LSTM branches with different time resolutions to capture a microcosmic burst mode and a macroscopic session behavior at the same time; the feature fusion module unifies the scale features to the same time sequence length and splices the scale features; the global dependence modeling module utilizes a multi-head self-attention mechanism to learn long-distance time sequence dependence; the dynamic weighted aggregation module highlights a key time slice through adaptive weight pooling; and the classification module outputs website category labels. According to the system, the recognition accuracy on a GTT23 data set is remarkably improved compared with that of an existing method, and good recognition capability and robustness are shown for various flow defense mechanisms.