5964 results about "Knowledge management" patented technology

An online social wager-based gaming system is disclosed, featuring dynamic cross-provider game filtering and persistent cross-provider voice-interactive group play. The system allows for automated multi-seat group game reservations and incorporates a distributed ledger for bet verification. Features include a Group Connect module for dynamic group formation and live audio across various game providers, enabling real-time play. A Professional Companion Connect module facilitates live webcam or microphone gambling sessions with professional companions, under contractual agreements. The User Games module enhances personalization by integrating user-uploaded images into the gaming environment. A cryptocurrency / blockchain-based bet tracking system ensures transparency and security in managing bet transactions through a controlled digital wallet system. This integrated platform aims to provide a cohesive, interactive, and personalized online casino experience, addressing limitations of traditional solitary online gaming by fostering social connections and enhancing user trust and engagement.

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

The Trust-Informed Engagement and Restraint (TIER) system is a modular behavioral governance architecture for conversational AI that enables dynamic, real-time enforcement of trust-aligned interaction policies. The system comprises a Behavioral Governance Framework defining policy rules and an Enforcement Wrapper hosting Core Modules that operate externally to the AI model. These modules regulate behavioral traits including trust calibration, emotional tone, conversational containment, authority modulation, and cross-modal consistency. TIER continuously monitors interaction metrics and applies policy-driven constraints during live sessions without requiring model retraining or internal access. Unlike static filters or post-hoc moderation systems, TIER provides proactive, session-aware behavioral governance with auditable enforcement across domains. The architecture supports model-agnostic deployment in regulated and sensitive environments such as healthcare, finance, legal services, and intelligent assistance platforms.

An Automated AI-Driven Lifestyle Orchestration System proactively manages a user's daily life by intelligently populating calendars with relevant, time-sensitive marketing objects. This is achieved through sophisticated AI-driven analysis of user directives, preferences, and real-time location data obtained via computing devices like smartphones. The system leverages advanced media identification modules employing fingerprinting and watermarking to accurately match user-captured media (via a Percipient Sample Pack (PSP)) to specific content and associated products. It facilitates dynamic commerce through hierarchical linked lists for purchasing authentic or similar items, supported by an affiliate program. This inventive solution significantly improves personal organization and digital commerce by transforming passive interaction into a proactive, intelligent, and monetizable user experience.

The invention discloses a medical health question and answer method and device based on an intelligent agent and a medium, and relates to the technical field of artificial intelligence medical question and answer, and the method comprises the steps: receiving an intention analysis report through a master control intelligent agent, accessing a dynamic dialogue context pool, and generating an intelligent agent cooperation instruction according to the state of the intention analysis report and the state of the dynamic dialogue context pool; performing credibility evaluation on the preliminary medical answer report by using a credibility calibration agent, generating a confidence score and an evidence conflict level, and performing multi-dimensional weighted fusion and risk mode recognition by using a dynamic risk evaluation strategy to generate a diversified disposal instruction; and when the diversified treatment instruction is issuing permission, performing safety compliance check on the preliminary medical answer report to generate compliance medical answers. According to the invention, multi-dimensional control of credibility and security of medical answers is realized, and finally the beneficial effects of providing personalized medical questions and answers and ensuring that information is real, reliable, compliant and safe are achieved.

An example operation may include at least one of storing first interaction content with a service provider; receiving second interaction content from a communication session between a source device and a service provider device of the service provider; identifying at least one contextual attribute associated with the source device; determining a response based on execution of at least one large language models (LLMs) on the second interaction content, the at least one contextual attribute associated with the source device, and the first interaction content with the service provider; and outputting the response to at least one of the source device and the service provider device during the communication session.

The present disclosure relates generally to a gaming system, device, and method supportive of rewarding responsible gaming behaviors. An illustrative method includes presenting a representation of the electronic game on a display device, where the representation of the electronic game includes displaying a plurality of game features, executing the electronic game, determining, during execution of the electronic game, that a player of the electronic game has taken an action that corresponds to a responsible gaming action, correlating the responsible gaming action to a reward for the player, and presenting information to the player that describes the reward for the player along with instructions for redeeming the reward.

The invention relates to the technical field of intelligent education, and discloses a personalized historical exercise recommendation and automatic correction system based on a large model, and the system comprises a cross-modal data collection module which is used for collecting character input, time behavior and interaction track data of a student in an answering process, and outputting a collection result to a cognitive map construction module; and the cognitive map construction module receives the acquisition result output by the cross-modal data acquisition module, and is used for generating a cognitive map representing the mastering degree of the students on the historical knowledge points and the relationship thereof based on the acquisition result, and sending the cognitive map to a cognitive drive recommendation module and an automatic correction module. The cross-modal data acquisition module is introduced, so that dominant content answered by the students is acquired, diversified recessive behavior data such as answering duration, editing and modifying tracks, mouse hovering positions and answering pauses of the students are further acquired, and the system can surpass traditional simple answering right and wrong judgment due to the multi-dimensional data capture capability.

A method of automatic pre-prompt generation includes receiving at least one user preference from a user device, modifying a system prompt for a machine-learning language model based on the received at least one user preference to generate a modified system prompt, providing the modified system prompt as an initial input to the machine-learning language model, receiving a natural-language text prompt provided by the user to a chat application on the user device, receiving a user identifier from the user device, querying a first database with the user identifier to retrieve first information, generating a representation of the first information and the natural-language prompt, querying a second database using the representation to retrieve second information, and generating a modified text prompt based on the natural-language prompt, the first information, and the second information.

A computer-implemented system for automated document generation receives user input and processes it through artificial intelligence models to create professional documents. The system combines user-provided information with specialized knowledge databases containing domain-specific requirements and formatting standards to generate enhanced processing instructions. Trained machine learning models process these instructions to produce contextually appropriate content that addresses specific technical and legal requirements. The generated content is formatted using configurable templates to create completed documents that meet professional standards. The system provides adaptive user interfaces that adjust functionality based on user expertise levels, supports multiple operational modes including guided and automated generation, learns from example documents to improve output quality, and enables comprehensive workflow management through network-accessible services. Applications include patent applications, legal responses, technical documentation, and other specialized professional documents requiring domain expertise and regulatory compliance.

A digital agent is pre-trained to be a digital proxy for a user. Taking on the persona (e.g., personality, mannerisms, preferences, knowledge, and in some cases, a realistic visual appearance and voice of the human), the digital agent can effectively act on behalf of the human. During a virtual meeting, the pre-trained digital agent can listen to what the team has to say, ask clarifying questions, answer questions on the human's behalf, and raise points the human would want the team to consider. Since the digital agent visually resembles, sounds like, and acts like the human, the digital agent appears much like other remote participants, thereby improving the meeting experience of the other attendees and facilitating meeting productivity in the absence of a human team member.

Various aspects disclosed herein are directed to intelligent advantage spin techniques implemented in wager-based games conducted on electronic gaming devices. The intelligent advantage spin techniques may be incorporated into wager-based slot games for offering players various types of re-spin opportunities via the use of Advantage Spin (AVS) credits, loyalty points, or game credits. During gameplay, the system provides real-time analysis of game outcomes, identifying strategic moments such as near-miss scenarios to dynamically present customized advantage spin offers to players. Players can leverage AVS credits to selectively re-spin individual reels and / or symbols. AVS credits may also be employed as promotional incentives, redeemable across different game themes or EGMs, and can persist across gaming sessions, different EGMs, different venues, etc. Integration with systems like TITO and player loyalty accounts ensures seamless credit management, allowing casinos to issue, track, and incentivize credits based on both gaming and non-gaming activities.

Methods and systems for segmenting a conversation session and providing context to a generative language model are described. A conversation history is maintained for an ongoing conversation session. The conversation history contains conversation segments, where each conversation segment is associated with at least one topic and includes previous message(s) in the conversation session. A new message is received for the conversation session, and topic(s) associated with the new message are determined. The conversation history is filtered based on relevance to the topic(s) associated with the new message. The filtered conversation history has a relevant conversation segment associated with a topic that is relevant to the topic(s) associated with the new message. A prompt is provided to a generative language model based on the filtered conversation history and the new message. A message is outputted based on output generated by the generative language model in response to the prompt.

A store employee assistance platform is provided that is enabled with generative artificial intelligence to deliver role-specific, context-aware responses to natural language questions submitted by users, including store employees. The platform includes a store employee assistance application with a chat interface through which a user may submit a question. The platform identifies the user's role, store location, and access level, and retrieves relevant enterprise content from a vector database and historical data store. A prompt engine constructs a contextualized prompt incorporating the user's identity and the retrieved information, and submits the prompt to one or more generative AI models. The resulting response is tailored to the user's responsibilities and delivered through the chat interface, providing real-time operational guidance specific to the user's role within the retail environment.

Systems and methods are provided for managing AI (Artificial Intelligence) agents interactions with electronic communications that are displayed at an electronic communications interface, such as an email interface. The systems parse electronic communications to determine whether they correspond to new or existing requests and actions to be performed when responding to the request(s). The systems also generate notifications identifying the set of actions with visual identifiers that visually distinguish the set of actions based on whether they have been completed or not and whether they need authorization to be completed. The systems also display selectable controls for controlling how the AI agent performs the actions.

A method for managing conversation history in an Al system is disclosed. A user message is received and full conversation history payload is retrieved from a memory service. The full conversation history payload includes one or more messages, summaries, or moments. A prompt budget is dynamically allocated, based on an available context window. The prompt budget determines token allocations for the messages, summaries, or moments from the full conversation history payload. A prompt is assembled for a language model by selecting conversation history elements to fit within the allocated prompt budget. The selecting balances between recent verbatim messages, summarized content of older messages, and relevant older moments. The prompt budget is iteratively adjusted and the prompt is iteratively reassembled as new information is added, from one or more language model outputs or tool calls, while maintaining the full conversation history payload in the memory service.

Various systems and methods are described implementing a multi-access edge computing (MEC) based system to realize MEC federation management and broker functions for MEC frameworks. In an example, performing edge federation management functions of edge computing systems, to establish a partnership among multiple edge federation managers as a federation, include: using system data attributes to establish the partnership; using authentication data attributes to enable the edge federation managers to securely authenticate; using authorization data attributes to enable the edge federation managers to perform authorization; using availability zone data attributes to define zones in the federation; and using management and settlement information data attributes to enable management of resources in the federation. Further operations include communicating the data attributes via respective connections with the edge federation managers, and the use of defined interfaces and operations.

A gaming system and method of facilitating personalized wager opportunities based on a user-selected fantasy sports team is disclosed. Players may first select athletes for a fantasy sports team. Based on the projected team score for the fantasy sports team selected by the player, a set of wager opportunities may be generated for that player. The wager opportunities may include a set of benchmark point levels and associated odds for the respective levels. Players can place wagers based on whether the actual total score of the fantasy sports team they selected exceeds one or more benchmark point levels and specify the amount to be wagered for each benchmark point level. Thus, a player can make wagers that are won or lost based on the performance of the player's fantasy team compared to the benchmark point levels, regardless of how other players' fantasy sports teams perform.

The invention discloses a data governance method and device based on an MCP protocol and a medium, and the method comprises the steps: obtaining a language instruction of a user through a data center regulation and control MCP client, determining a data governance demand according to the language instruction, and determining an obtaining request according to the data governance demand; and sending the acquisition request to the MCP server to acquire the data resource through the MCP server, and performing data processing according to the data resource. The data governance process is started through the natural language instruction, user operation is facilitated, and the use threshold is lowered. And the data governance demand and the acquisition request are accurately determined through the analysis instruction, so that the governance pertinence is improved. And resources are obtained and processed by means of the MCP server, so that efficient data management is realized. According to the process, user requirements and data acquisition and processing links are integrated, so that data management is more convenient, accurate and efficient.

As disclosed herein, a computer-implemented method for travel planning is provided. The computer-implemented method may include receiving, via a conversational user interface (UI), a user input associated with a product offered by a booking application. The computer-implemented method may include retrieving, from a database associated with the booking application, at least one attribute of the product. The computer-implemented method may include determining, using a first machine learning (ML) model of a plurality of ML models, a user intent associated with the user input. The computer-implemented method may include generating, based on the at least one attribute and the user intent, a first response to the user input. The computer-implemented method may include providing, via the conversational UI, the first response to the user input. A system and a non-transitory computer-readable storage medium are also disclosed.

The invention discloses an intelligent multidisciplinary clinical consultation system and method based on a large language model, and relates to the technical field of medical artificial intelligence. According to the structured consultation suggestion set, the association degree value of the possible disease causes and the consultation departments is calculated in combination with the medical knowledge graph, the departments participating in the consultation are automatically matched, and the consultation sub-targets are determined, so that the problem of lack of interdisciplinary knowledge integration and dynamic coordination ability in the prior art is solved, and the situation that diagnosis and treatment only depend on a single subject is avoided; meanwhile, a multi-disciplinary consultation set is formed by counting the disease cause matching number, calculating the treatment emergency value and the priority index, determining the consultation sequence of consultation departments, obtaining consultation content according to matching of consultation sub-targets and clinical guidelines, and determining the application treatment scheme in combination with patient replies and historical treatment records; according to the process, multidisciplinary knowledge is integrated, comprehensive diagnosis and treatment suggestions are provided for the patient, and the defects of the prior art on a multidisciplinary cooperation overall solution are overcome.

Processing circuitry of a learning platform may be configured to maintain a graph database describing student learners. Processing circuitry may obtain new student learner data and load the data into the graph database. Processing circuitry may receive an engagement or interaction from the new student learner and responsively extract new learnings about the new student learner which are loaded into the graph database. Processing circuitry may receive an inquiry from the new student learner and in response, extract the new student learner data and the new learnings from the graph database and contextualize, using a large language model, a learning unit from the educational content provided by the learning platform as a response to the inquiry using the new student learner data and the new learnings. Processing circuitry may further return the learning unit contextualized by the large language model to the new student learner.

The invention discloses a tourism service agent system and method based on a multi-modal large model. The system comprises five parts: a user interaction interface, which is used for receiving a user request and returning a response; the agent center is used for performing intention understanding, task planning and response generation through a multi-modal large language model; and the tool calling module is used for executing specific API business operation. According to the intelligent tourism service system, the work of each module is coordinated through the intelligent agent center, a complete closed loop from user intention understanding to service execution is realized, accurate, reliable, whole-course and personalized intelligent tourism service can be provided, and the problems that a traditional tourism service system is single in function, inaccurate in information and lack of action ability are effectively solved.

The invention provides an anesthesia virtual simulation training system fusing knowledge, skills and a thinking closed loop. The anesthesia virtual simulation training system comprises a medical knowledge base module, a clinical thinking module, a skill training module, an examination question brushing module, a knowledge graph module and an intelligent platform bottom layer framework. The intelligent platform underlying architecture comprises a data middle platform, an AI engine and a 3D engine, collects student behavior data of each module, constructs a dynamic student ability portrait through a gradient boosting tree algorithm and a collaborative filtering recommendation model, analyzes knowledge blind areas and skill shortages, plans a personalized learning path and pushes targeted training content, and provides a personalized learning result. A closed-loop process of evaluation, learning, practice and re-evaluation is formed; and deep fusion of theoretical knowledge, clinical thinking and skill operation is realized through a cross-module collaboration mechanism. The problems that traditional anesthesia teaching is high in practical operation risk, scattered in resource and insufficient in individuation are solved, and the clinical comprehensive ability and teaching quality of anesthetists are effectively improved.

The invention relates to a simulation dialogue partner training system based on a large model. The simulation dialogue partner training system comprises a product knowledge base module, a question and answer library construction and management module, a pair training simulation module, a stage control module, a supernatural voice dialogue module, a verbal skill prompt module, a real-time evaluation module and a dialogue summary report module. The intelligent partner training system for customer communication training has high simulation dialogue ability, flexible configuration ability and a perfect evaluation feedback mechanism, can effectively replace a traditional scripted training or real person simulation partner training mode, and improves the communication actual combat ability of front-line personnel such as sales personnel and customer service personnel. According to the invention, low-efficiency links in a traditional training mode are replaced by an intelligent means, the training quality, the standardization degree and the reproducibility are improved, an enterprise is finally assisted to create a more professional and efficient customer front-line team, and the system can be widely applied to scenes such as enterprise training, new employee on-duty training and product popularization preparation.

The invention belongs to the technical field of medical treatment and public health, and particularly relates to a hypertension group knowledge recommendation method and system based on a large language model multi-agent. Hypertension knowledge question-answer pair information, medical short video information and user personal health portraits are finely extracted by constructing a hypertension knowledge question-answer pair library; according to the method, video content quality evaluation and matching degree evaluation are performed, and user platform interaction data adjustment is combined, so that personalized and accurate knowledge recommendation services can be provided for hypertension users, the requirements of hypertension patients for health knowledge are met, the accuracy and effectiveness of knowledge recommendation are improved, and self-health management of the patients is facilitated.

The disclosed concepts relate to automatically identifying conditions in a video game to trigger a help session. When a help session is triggered, another video game player or machine learning model can temporarily take over for the current video game player until an ending condition is reached. Help session triggering can be designated by evaluation of prior gameplay data of other video game players to identify in-game conditions that may tend to cause user disengagement, such as in-game conditions that are associated with difficult in-game goals or negative in-game consequences.

An autonomous communication system includes a language model, a retrieval module, a caching mechanism, an autonomous agent, and a human interface for managing interactions and responses. A method and computer-readable medium for managing communication also include these components for processing, enhancing, summarizing, managing interactions, and allowing human intervention.

The invention relates to the technical field of smart home, and discloses a smart home environment regulation and control method and device based on multi-modal behavior perception, and the method and device can understand the home environment parameter preference of a user in different scenes through a home habit reference value. The current physiological state, behavior mode and environment condition of the user can be comprehensively captured by collecting multi-mode sensing data. And calculating a multi-modal data deviation value to quantify the difference between the current home environment and the user habits, and positioning environment factors needing to be adjusted. The multi-modal data deviation value is subjected to weighted fusion calculation according to the weight matrix driven by the current health state of the user, and the comfort degree deviation index is generated, so that the recognition accuracy of user requirements is improved, and personalized and dynamic comfort degree evaluation is realized. An intelligent regulation and control strategy is determined according to the comfort degree deviation index, precise regulation and control of the home environment in the fields of medical science and technology and home-based care for the aged are achieved, and the accuracy and adaptability of home environment parameter regulation and control are effectively improved.

The invention relates to the technical field of intelligent financial evaluation, and discloses a news recommendation method, device and equipment based on an LLM big language model.The news recommendation method comprises the steps that initial recommendation news data and historical recommendation news data are obtained, and a basic data set is provided for subsequent analysis; extracting interaction data of the user for historical news from the historical recommended news data, and constructing a historical interaction database of the user and the historical news; basic information, interest tags and financial risks of the user are synchronously extracted, a user database is constructed, and a structured user portrait is formed; and inputting the initial recommended news data and the historical recommended news data into the BERT model. The method can be applied to the development of business systems such as financial science and technology, medical health, old-age care and the like, and through the strong context understanding capability of the LLM, the nuance of news contents and the specific requirements of users can be better captured.