10 results about "Shared knowledge" patented technology

We provide the system. [Solution] A means of acquiring knowledge from elderly people as voice or text data using speech recognition technology, A method for analyzing the acquired data using natural language processing algorithms and classifying it into general themes, A means of storing classified data on a digital information storage medium and providing it to users as needed, A means of providing an interface for sharing knowledge about the elderly among caregivers, A system that includes this.

The application provides a large model-oriented distributed computing power scheduling method and related device, the method comprises: obtaining an agent task request and task data, the request comprising computing power demand, data sensitivity level and memory calling demand; based on the data sensitivity level and the computing power demand, determining the computing power source as edge computing power or public cloud computing power; if it is edge computing power, issuing a task scheduling instruction to the edge computing power node to control its exclusive allocation and release the computing resources after completion; if it is public cloud computing power, routing the task to a public cloud node; based on the memory calling demand, controlling the execution node to write the task execution memory with a timestamp into a shared knowledge base to trigger the knowledge base to perform time sequence sorting and gradient degradation processing. The application realizes the shunting of heterogeneous computing power, safeguards data privacy while preventing resource preemption of edge multi-task concurrency, and realizes the sharing and storage release of context features through the memory degradation mechanism.

This application provides a self-regulating dialogic multi-agent system and interaction method based on dynamic topology. The system includes: a scheduling module, used to receive user input and route tasks to corresponding domain task agents under normal conditions; several domain task agents, used to process the received tasks and evaluate the cognitive state in real time, and issue assistance signals when the cognitive state meets preset conditions; a shared knowledge management module, used to maintain a dynamically updated distributed semantic knowledge graph; wherein, the distributed semantic knowledge graph is used to share, associate and persist the structured knowledge entities and context information generated during the conversation in real time among all modules; and a topology control module, used to dynamically switch the communication control topology of the system from a first topology to a second topology in response to the received assistance signal; and to restore the communication control topology from the second topology to the first topology when the assistance signal is eliminated.

The application belongs to the technical field of wireless communication, and discloses a phase shift feedback method of a reconfigurable intelligent surface. The method is applied to a sending device, and the phase shift feedback method of the reconfigurable intelligent surface comprises the following steps: obtaining a to-be-transmitted phase shift matrix; determining a feature serial number according to the to-be-transmitted phase shift matrix, a target encoder and a shared knowledge base, wherein the shared knowledge base is common to the sending device and a reconfigurable intelligent surface device; and sending a bit stream of the feature serial number to the reconfigurable intelligent surface device, so that the reconfigurable intelligent surface device determines a received phase shift matrix according to the bit stream of the feature serial number, the shared knowledge base and a target decoder. In the foregoing manner, the feature serial number of the to-be-transmitted phase shift matrix that needs to be fed back is determined, and only the bit stream of the feature serial number is transmitted during transmission, so that the communication resources occupied by the feedback of the reconfigurable intelligent surface and the feedback data volume are greatly reduced, the time resources consumed during the feedback are reduced, and the phase accuracy of the feedback is ensured.

A system for crowd-sourced media insights and predictive analysis is disclosed. Electronic devices capture media representing a real-world environment and associate it with user-generated insights. A processing unit converts the media into unique identifiers to store and retrieve these insights from a database, enabling users to access shared knowledge by capturing similar content. Additionally, the system analyzes live-streamed video using machine learning to predict subsequent events and transmit alerts or predictive insights to the user in real-time.

17. Abstract of description Provided in the embodiments of the present application are a knowledge base processing method and apparatus, and a computer device, a medium and a program product. The knowledge base processing method comprises: receiving a sharing credential of a shared knowledge base; in response to an access operation on the sharing credential, displaying the shared knowledge base, which is shared, wherein the shared knowledge base comprises at least one knowledge file; receiving question information for the shared knowledge base; and displaying answer information for the question information, wherein the answer information is obtained by means of performing answer generation on the question information on the basis of the knowledge file in the shared knowledge base. By means of the embodiments of the present application, the knowledge utilization rate of a knowledge base can be increased.

A computer-implemented digital knowledge management system for institutional learning and decision support, comprising the following: A user interaction interface configured to receive structured institutional information from a variety of users connected to a university. This structured institutional information includes strategic issues, institutional goals, performance indicators, academic activity data, and decision-relevant input. an input processing unit that is operationally connected to the user interaction interface and is configured to capture, classify, and convert the received structured institutional information into machine-readable data sets; a collaborative culture assessment unit consisting of at least one processor and a memory in which executable instructions are stored, wherein the collaborative culture assessment unit is configured to collect and process organizational behavior data representing loyalty, engagement, cohesion, well-being and sense of community among members of the institutional leadership; a knowledge generation unit that is operationally linked to the collaborative culture assessment unit, wherein the knowledge generation unit is configured to analyze received knowledge records and generate new institutional knowledge by exploring alternative ideas, identifying new insights, and combining individual and collective institutional contributions; a knowledge exchange unit that is communicatively linked to the knowledge generation unit, wherein the knowledge exchange unit is configured to distribute the generated institutional knowledge to authorized users via controlled communication channels and structured knowledge dissemination procedures; a knowledge application unit designed to transform distributed institutional knowledge into decision support tools, including proposed strategic actions, operational recommendations, and measurable performance targets; an institutional learning repository consisting of a permanent digital storage system configured to store knowledge records, decision outcomes, institutional experiences, and insights gained from implemented decisions; a decision quality assessment processor that is operationally linked to the institutional learning repository and the knowledge application unit and is configured to evaluate generated decisions against predefined institutional criteria, including problem-solving effectiveness, strategic value contribution, achievement of institutional goals, and contribution to organizational learning; and a coordination processor configured to coordinate the operational interaction between the collaborative culture assessment unit, the knowledge generation unit, the knowledge sharing unit, the knowledge application unit, the institutional learning repository, and the decision quality assessment processor, such that the collaborative organizational conditions influence knowledge generation, knowledge distribution, knowledge utilization, and the subsequent evaluation of strategic decisions.

The application discloses a kind of based on deep learning data security detection method and system, it is related to information security technical field, it solves the technical problem that the detection accuracy of data security detection method is lower in prior art, usually by multiple independent modules to form detection system, independent of each other between module, and cannot share knowledge and mutually corroborate, difficult to form unified threat situation awareness, the detection accuracy of data security detection method is lower;Feature representation vector is generated based on multi-modal original data;The feature representation vector is input into dynamic weighted multi-task detection model to obtain detection result;Risk assessment report is generated based on detection result, and multiple related security detection tasks are integrated into a unified deep learning model to obtain a dynamic weighted multi-task detection model, the model can give multiple angle detection results simultaneously, these results mutually corroborate, provide more abundant and more reliable basis for final risk assessment, improve the detection accuracy of data security detection method.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for sharing knowledge graphs. One of the methods includes receiving a first identifier of a data source from a first client device and extracting a key phrase from the data source. The key phrase is added to a knowledge graph for a shared space. A second client device with access to the shared space submits a query to the shared space. A response to the query is generated using one or more key phrases from the knowledge graph for the shared space. The response is provided to the second client device.