4results about How to "Break down data barriers" patented technology

This invention proposes a data fusion and intelligent recommendation method and system for digital economy empowerment in the cultural tourism industry. The method includes: performing distributed data collaborative modeling based on local differential privacy and federated learning to aggregate features from multiple sources of cultural tourism data while protecting privacy; constructing a dynamic knowledge graph that integrates visual semantics and spatiotemporal state, generating spatiotemporal evolution embedding vectors through cross-modal attention mechanisms and dynamic graph neural networks; constructing a twin simulation space mapping physical scenes, performing counterfactual inference based on sequence prediction models; generating a recommendation list using a deep reinforcement learning policy network, conducting virtual pre-runs in the simulation space, and iteratively optimizing the strategy based on feedback risk-reward indicators. This invention solves the problems of isolated cultural tourism data, semantic bias in recommendations, and lack of consequence pre-running, achieving intelligent decision-making that balances privacy security, recommendation accuracy, and overall operational efficiency.

This application relates to a work order fusion processing method, electronic device, and storage medium. The method includes: acquiring work orders from multiple business systems to form a work order set; performing work order aggregation processing on the work order set to obtain a fused work order set; performing task filtering and reorganization processing on each fused work order in the fused work order set to obtain a target work order set; determining a work order processing sequence based on the target work order set and preset priority rules; determining dispatch constraint rules based on operator factors; dispatching work orders according to the work order processing sequence and dispatch constraint rules; receiving work order execution results and feeding them back to the corresponding business system. The solution provided by this application can improve the work order processing efficiency of on-site operators.

The invention belongs to the technical field of artificial intelligence, and discloses a data analysis method, device and equipment and a storage medium, and the analysis method comprises the steps: based on a unique identifier of a target entity, associating different types of data streams of the target entity, and constructing an entity data view corresponding to the target entity; generating a first type of quantization attribute of the first type of data stream directly bound with the unique identifier; extracting a feature vector representing the behavior intensity of the target entity in the whole life cycle from the entity data view; for a second type of data stream, inputting the feature vector and the second type of data stream into the intelligent sharing model, and outputting a second type of quantization attribute corresponding to the second type of data stream; and fusing the first type of quantitative attributes and the second type of quantitative attributes to obtain a comprehensive state index of the target entity. The method can be applied to business management systems of financial science and technology, medical health and the like, and solves the technical problem that in the prior art, the associated data of the data indexes cannot be fully mined, so that accurate alarm based on the data indexes cannot be realized.

The invention relates to a multi-modal museum management agent system based on a large language model, and belongs to the technical field of deep learning. According to the system, images, voices, texts and environment data are collected and processed through a multi-modal perception and fusion module, deep semantic analysis is carried out through a big language model semantic center, and structured semantic representation is generated; the multi-agent decision scheduling module dynamically schedules guide service, cultural relic management, academic research and environment regulation and control agents according to task types, and coordinates decision conflicts; and the execution and interaction module converts the decision result into a natural language response, a multi-modal content and an equipment control instruction. The system solves the problems that an existing museum management system is separated in function, data barriers exist, and the multi-mode cooperation capability is insufficient, and intelligent fusion and efficient response of exhibit management, visitor service and academic research are achieved.