860results about "Web data navigation" patented technology

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

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.

Disclosed are embodiments of a system and method for baling recyclable materials and managing the baling of recyclable materials. The apparatus for baling includes a baler for compressing and baling recyclable materials, a scale, label printer, and a processor. Certain embodiments further comprise at least one digital camera, RFID dispenser, and an internet connection that allows the processor to transmit collected data to a remote database for further analysis.The disclosed method for baling recyclable materials comprising the steps of baling materials; weighing the bale automatically using a digital scale operably connected to the processor; recording the weight of the bale automatically; and printing a label which displays the recorded weight of the bale. Additionally, the method may comprise inputting information and / or automatically recording data, and / or automatically transmitting the data associated with a bale to a remote database.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

An embodiment detects by a Clustering Component of a Recommendation System, a candidate content based on a user query, responsive to the detected candidate content, executes a clustering algorithm on the detected candidate content to output a cluster and a cluster result. The embodiment decides, by a Recommendation Clarification Component of the Recommendation System, to recommend a clarification based on the cluster result, comprising computing a distance between a cluster and a response of a large language model to the user query where an option list is updated with the clarification where the clarification is based on the cluster and the distance. The embodiment also detects by the Recommendation System a selection in the option list, responsive to the detected selection, generates a prompt based on the selection where the prompt is inputted into the Recommendation System and the large language model.

Systems and methods for proactive query and content suggestion can include obtaining web data, determining a change event occurred, and generating a query and content suggestion. Generating the query and content suggestion can include processing data descriptive of the change event with a generative model to generate one or more model-generated query suggestions. One or more web resources can be obtained then processed to generate a change event summary. The one or more query suggestions and the change event summary can then be provided for display.

The invention discloses a navigation switching method and device for a product module, and relates to the technical field of modular navigation switching, and the method comprises the following steps: generating a user permission model according to user information, and generating a navigation bar according to the user permission model; capturing a click event of a user, and initiating a module switching request according to a module corresponding to the navigation item; querying the dependency relationship of the modules after receiving a module switching request, loading the resources of the dependent modules according to the dependency relationship, loading the core resources of the target module after the loading of the resources of the dependent modules is completed, and displaying the basic layout; when the basic layout is displayed, the dynamic data and the secondary resources are loaded in parallel, the page is filled with the core data, and module display is completed. According to the invention, the problems of low module switching efficiency and redundant resource loading in the prior art are effectively solved, and the user experience and resource management are optimized.

The invention discloses a website navigation method based on artificial intelligence, and the method comprises the steps: extracting entry information currently searched by a front-end page user, historical search record data of the user and ip address data of the user, carrying out the keyword division of the obtained historical search record data, obtaining historical keywords, and storing the historical keywords in a database; the method comprises the following steps: searching entry information, processing according to the searched entry information to obtain entry keywords, retrieving associated keywords in a system library according to the entry keywords, semantically integrating each keyword and the associated keywords into a long-tail keyword, searching according to the long-tail keyword, and evaluating the entry information through an evaluation algorithm. According to the method, the search items are sorted according to the analysis result, the final result is sent to the search page, the search result is automatically fed back to the back-end server, the user feeds back the opinion of the search result based on the opinion interface established by the background server, and the retrieval accuracy and the user satisfaction degree are improved.

The invention provides a vehicle enterprise APP intelligent assistant navigation method and system based on a large model. The method relates to collection of user navigation requirements and identification of key entities and user intentions by using a large language model. And when the navigation intention is identified, generating a navigation route through map data and a path planning algorithm in combination with the current position and the target position. And when the vehicle control intention is identified, remotely controlling the vehicle through a vehicle control interface. And when the intention is identified as the information query intention, relevant information is retrieved and displayed from the vehicle information base. And collecting user feedback, an optimization model and a navigation strategy. The navigation demand information comprises text and voice information. The navigation requirement understanding of the user is improved through the large language model, tedious operation is avoided, and the access efficiency and the user experience are improved. Personalized and real-time recommendation is realized, real-time information is provided according to requirements and environments, and travel route planning is optimized. Dialogue management supports multiple rounds of dialogues and deep interaction, complex requirements are effectively processed, and the ability to deal with complex scenes is improved.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

The present specification describes systems and methods of generating and displaying at least one context aware active icon, virtual or graphical user interface object based on contextual and / or user attribute data acquired in response to a user using an application program or accessing a website / webpage on their computing device. In various embodiments, the at least one virtual object is visually overlaid on top of the application program or the website / webpage. The at least one graphical user interface object includes a URL or pointer directed towards launching another application program, evoking a functionality of another application program and / or launching another website / webpage on the user's computing device.

The present disclosure relates to a book search method, apparatus, device and storage medium. In the method, target search content is received. A plurality of recommended book categories associated with the target search content and book information corresponding to respective recommended book categories are obtained. A book aggregation card is generated based on the respective recommended book categories and the book information, and the book aggregation card is displayed on a search result page. According to the embodiments of the present disclosure, the user can directly view, on the search result page, the plurality of recommended book categories associated with the target search content and the book information under each recommended book category. Therefore, the user search cost is reduced, the book search flow is simplified, and the book search efficiency is improved.

A computing system is provided including processing circuitry configured to implement a ranker module configured to jointly compute relevance scores of a set of candidate keywords to a query, and to generate a ranked list of candidate keywords based on the relevance scores. The ranker module includes a cross attention encoder configured to jointly compute the relevance scores by obtaining contextual embeddings for query tokens in the query and union of keyword tokens in the set of keywords, selectively pooling the contextual embeddings for the query tokens and the union of keyword tokens, inputting the selectively pooled contextual embeddings into a classifier that has been trained to predict a relevance score of the plurality of keywords to the query based on the contextual embeddings to output a relevance score for each query-keyword pair for the keywords in the set of candidate keywords, and outputting the ranked list of candidate keywords.

A method for displaying an application, includes: determining, in response to receiving by the electronic device a first operation on a target application, a first display window for the target application; determining a first display window parameter of the first display window, and determining, based on the first display window parameter, a target layout framework corresponding to the target application; and displaying the target application in the first display window based on the target layout framework.

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and / or request bodies, structuring user-generated content, and / or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and / or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

A system for generating a video based on historical visits to a website is disclosed. The system determines that a first user wants to perform a first task on the website. In response, the system detects a navigation path that is being traversed thought the website and associates the navigation path with the first task. The system generates a first video that comprises one or more video scenes of visited sections. The system detects that a second user wants to perform the first task on the website. In response, the system fetches a code portion associated with the sections, generates one or more video scenes based on the fetched code portions, and generates a second video that comprises the one or more video scenes. The system displays the generated video on the website, where the second video shows the navigation path to perform the first task on the website.

Systems and methods are disclosed for integrating with third-party applications. An extension module operates with a user interface application on a client computing device. The extension module enables integration of functionality of an associated middleware system. The extension module extracts data from a user interface of a third-party application system based on a regular expression template. The extension module transmits data to the middleware system and receives information from the middleware system. The extension module can alter at least a portion of the user interface based on the information received from the middleware system.

The invention discloses a feature extraction method and system for user access behavior data, and relates to the technical field of user access behavior data analysis. The user access behavior data focuses on current page residence time data and mouse sliding track data; if the residence time is larger than the minimum residence time threshold value, user access behavior data need to be collected, the user access behavior data are mainly data related to mouse movement, and mouse sliding track data can reflect a main concern area of the user on the current page; according to the method, the focus of a user in the process of browsing a current webpage is accurately obtained through analysis of mouse sliding track data, so that targeted pop-up window guide recommendation is realized, and historical interest portrait data of the user can be formed by recording pop-up window guide recommendation data of the webpage browsed by the user every time for the same user; the accuracy of user access behavior analysis is greatly improved, and user disgust caused by broad irrigation type recommendation is avoided.

Various embodiments of the present disclosure provide a refined query resolution based on relevant search clustering using real time data. The techniques may include receiving a prefix text input associated with a search query, identifying a preceding text input associated with a historical search query preceding the search query, identifying a plurality of relevant search clusters from a clustered hierarchical tree based on the prefix text input and the preceding text input, identifying one or more search labels for the search query from the plurality of relevant search clusters, and initiating the performance of a query resolution operation for the search query based on the one or more search labels.

There are provided systems and methods for a guided web crawler for automated identification and verification of webpage resources. A service provider, such as an online transaction processor, may provide a guided web crawler and / or resources for such crawler for execution by computing devices of users. Users may load different pluggable modules to the guided web crawler, which are associated with specific web crawling tasks. Web crawling tasks may correspond to identification and verification of webpage resources on a webpage, such as a location, placement, use of, and / or number of appearances of the resource. The web crawler may use code from the pluggable module being executed to parse and / or crawl webpage data for a webpage and identify requested resources. Thereafter, the guided web crawler may automate resources to use, display, and / or interact with the identified and verified resource.