18 results about "Content discovery" patented technology

Technology is disclosed for dynamically creating and / or validating new URLs based on a user's query and / or contextual data. This enables the discovery of relevant content that may not be pre-existing in the search engine's index. This process enhances the search engine's ability to deliver the most current and relevant results by generating potential content sources in real-time, validating them, and incorporating the discovered content into the index for immediate query execution. Various embodiments are additionally or alternatively directed to a process that involves iteratively discovering, crawling, and indexing new content by following links from seed URLs, which may be either pre-existing or generated. This process deepens the search engine's index by continuously exploring outlinks, fetching new content, and updating the index in real-time.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real-world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

Disclosed are computerized systems and methods for a decision intelligence (Dl)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real -world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real-world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

Processor-based systems and / or methods of operation may generate queries and suggest legacy narrative content (e.g., video content, script content) for a narrative under development. An artificial neural network (ANN, e.g., autoencoder) is trained on pairs of video and text vectors to capture attributes or nuances beyond those typical of keyword searching. Query vector representations generated using an instance of the ANN may be matched against candidate vector representations, for instance generated using an instance of the ANN from legacy narratives. Such may query for missing video and / or text for a narrative under development. Matches may be returned, including scores or ranks. Feature vectors may be shared without jeopardizing source narrative content. Legacy source narrative content may remain secure behind a controlling entity's network security wall.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real-world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

According to one aspect of the present disclosure, a method of thumbnail personalization is provided. The method includes initializing a thumbnail-personalization engine that includes a multi-armed bandit (MAB) model. The method includes allocating first user traffic to the plurality of thumbnails. The method includes calculating a first thumbnail-conversion rate of each thumbnail of the plurality of thumbnails based on performance data associated with the first user traffic. The method includes allocating second user traffic to the plurality of thumbnails based on the first thumbnail-conversion rate. The method includes calculating a second thumbnail-conversion rate of the plurality of thumbnails based on performance data associated with the second user traffic. The method includes determining an updated set of parameters for each arm of the MAB model based on a data decay function or a sliding-window period applied to the first thumbnail-conversion rate and the second thumbnail-conversion rate.

Technology is disclosed for dynamically creating and / or validating new URLs based on a user's query and / or contextual data. This enables the discovery of relevant content that may not be pre-existing in the search engine's index. This process enhances the search engine's ability to deliver the most current and relevant results by generating potential content sources in real-time, validating them, and incorporating the discovered content into the index for immediate query execution. Various embodiments are additionally or alternatively directed to a process that involves iteratively discovering, crawling, and indexing new content by following links from seed URLs, which may be either pre-existing or generated. This process deepens the search engine's index by continuously exploring outlinks, fetching new content, and updating the index in real-time.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real-world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

A method, apparatus, and product comprising: loading a webpage at a Content Management System (CMS) platform, the page comprising page elements presenting manually curated content; executing a policy editor displaying management tools configured for defining a webpage policy that assigns to each page element an editorial control level selected from a manually curated control level, a manually curated de-duplication control level, and a personalized control level; incorporating code representing the webpage policy into the webpage; and publishing the webpage for execution on end devices, wherein execution of the code causes replacement of manually curated content with personalized content items from a third-party content discovery server based on assigned control levels and constraints preventing content duplication within the webpage.

The invention relates to the technical field of text processing, in particular to a target content analysis method and system based on an AI model, and the method comprises the following steps: carrying out the preprocessing of an initial large-scale data set, and obtaining a first intermediate data set of the initial large-scale data set; performing duplicate removal processing on the first intermediate data set to obtain a second intermediate data set; obtaining a final event information set based on any second intermediate data set and a preset large model; it can be known that through the multi-dimensional data preliminary screening and high-performance vector retrieval technology, the target content discovery efficiency is greatly improved, and redundant information is greatly reduced; meanwhile, based on a large language model and a dynamic prompt generation technology, a classification system which can be rapidly deployed and adjusted without a large number of training samples is realized.

Disclosed are computerized systems and methods for a decision intelligence (DI)-based framework that automatically and / or dynamically provides an interactive content viewing and content discovery experience to users. The framework includes functionality for real-time video content analysis and interactive entity identification that, inter alia, provides novel capabilities to viewing users related to the extraction, analysis and subsequent interaction with content depicted within video frames during playback of such content. The framework implements artificial intelligence / machine learning (AI / ML) approaches for video processing, user interaction and information delivery through a series of interconnected processes and subsystems. In some implementations, rendered content can be parsed and mined for real-world and / or digital content depicted therein that relate to real-world entities and / or digital resources, whereby interaction with such entities is provided in the form of a provided interface, electronic message and / or recommendations for further information discovery, or some combination thereof.

The disclosed techniques can overcome challenges that arise when large language models are used for summarizing documents that exceed the token limit of a LLM. The disclosed techniques communicate contextually relevant segments of a document with customized prompts to an LLM for generating a summary. A subset of segments can be selected from a document based one or more factors, including but not limited to, a token count of content of the select segments, a determination that the token count of content of the select segments does not exceed a token limit of the large language model. The subset of segments can also be selected based on a determination that the selected segments meet one or more criteria with respect to specific user activity. Thus, the system can also provide technical solutions that can use an LLM to discover content of interest stored in large files.

The invention discloses a method and a system for triggering a collaborative editing space based on a geographic position and a social relationship, and relates to the technical field of collaborative editing, and the method comprises the following specific steps: a user terminal judges a triggering condition through a positioning report position and a geofence service, and sends an event to an application server if the triggering condition is met; the server verifies the social relationship, screens visible space-time capsules and notifies the terminal; the server verifies the authority for the second time when the terminal previews and checks; according to the method, the geographical fence and the social relation verification are combined, accurate triggering and personalized display of the content are realized, the timeliness and the correlation of content discovery are improved, and meanwhile, the method has the advantages that the user can edit the content, the version is updated, the terminal is updated and displayed, and the user experience is improved. A multi-dimensional editing authority control and version priority algorithm is introduced, the problem of multi-user concurrent editing conflicts is solved, multi-type content editing is supported, the collaborative creation efficiency is improved, and team collaboration in a geographic scene is supported.

A system is disclosed that integrates a context-aware, domain-specific artificial intelligence architecture into a location-based or interest-based peer-to-peer communication platform. The system improves operation of such platforms by enabling streamlined content discovery, enhanced personalization, efficient user and group administration, and dynamic content and user moderation with minimal computational requirements. Technical improvements include leveraging a pre-trained language model in conjunction with a procedural function framework, semantic search, and content retrieval modules to generate context-aware responses without resource-intensive retraining. The architecture supports classification, parameter extraction, and sentiment analysis to provide accurate and scalable query handling while reducing latency and computational load.

A system is disclosed that integrates a context-aware, domain-specific artificial intelligence architecture into a location-based or interest-based peer-to-peer communication platform. The system improves operation of such platforms by enabling streamlined content discovery, enhanced personalization, efficient user and group administration, and dynamic content and user moderation with minimal computational requirements. Technical improvements include leveraging a pre-trained language model in conjunction with a procedural function framework, semantic search, and content retrieval modules to generate context-aware responses without resource-intensive retraining. The architecture supports classification, parameter extraction, and sentiment analysis to provide accurate and scalable query handling while reducing latency and computational load.