2 results about "Knowledge representation and reasoning" patented technology

The application discloses a kind of city resilience dynamic early warning method and system based on knowledge graph, belong to knowledge representation and reasoning technical field, specifically as follows: obtaining the crowd distribution data of carrying multiple personnel identity tags during target activity, and the operation state data of target facility;The above data is respectively loaded to the service layer and the physical layer of the preset knowledge graph, obtain the initial state value of each node, and determine the dependence intensity coefficient of mapping relationship from the personnel identity tag of load node in the support scheme;Receive target disturbance event and determine disturbance node;Disturbance node, initial state value and dependence intensity coefficient are input into pre-trained graph neural network model, with dependence intensity coefficient as cross-layer edge weight, perform alternating state update between physical layer and service layer until the preset convergence condition is met, to generate city resilience early warning signal.Therefore, by implementing the present application, the accuracy of city resilience early warning under major activity support scenario can be improved.

The present application relates to the technical field of artificial intelligence, and provides a large language model retrieval augmentation solution. In the present solution, text data of a target vertical domain is acquired, and a domain knowledge graph containing entities, attributes and entity relationships is constructed, so as to implement professional knowledge structured representation; and a large model auxiliary component is trained by means of a deep learning model, so as to assign a domain entity recognition capability and a question intent recognition capability to the large model auxiliary component. The trained large model auxiliary component is integrated into a target large language model to enable a vertical domain semantic parsing capability. The domain knowledge graph provides domain fine-tuning information to perform domain fine-tuning on the target large language model to generate a retrieval augmented large language model. The retrieval augmented large language model performs vertical domain professional question parsing, key entity identification and knowledge retrieval within the range of artificial intelligence technologies such as semantic understanding, knowledge representation and reasoning, natural language processing, probabilistic reasoning and cluster analysis, and supports multiple types of professional knowledge question answering and intelligent retrieval scenarios.