3results about How to "Easy performance analysis" patented technology

The invention discloses a named entity recognition method and system based on a knowledge enhancement pre-training model, relates to the technical field of named entity recognition, and aims to solve the problem that an existing training model cannot perform named entity recognition more accurately. According to the method, the knowledge enhancement pre-training model is introduced, so that the model can learn more priori knowledge and semantic information, the generalization ability of unseen text data is improved, the interpretability of the model is enhanced through the detailed performance evaluation and optimization process, the working mechanism of the model is beneficially understood, and the working efficiency of the model is improved. Therefore, the model is better adjusted and optimized, the generalization ability of the optimized model is also improved, the model can better adapt to different application scenes and data sets, the generation of the monitoring log enables performance analysis and problem tracking to be more convenient, the continuous optimization of the model performance is facilitated, and the optimization efficiency is improved. A standard knowledge enhancement training model can be improved according to user feedback on a target application terminal.

The invention discloses a data mining method based on public safety events, relates to the technical field of data mining, and solves the technical problems that it is difficult to fully analyze data, when the amount of retrieved data is too large, it is difficult to comprehensively analyze the relevance of the data, and it is not convenient to quickly lock the data with stronger relevance to safety time while comprehensively retrieving a large amount of related data; the method comprises the following steps: obtaining multimodal data from different sources, including public area monitoring data, radar sensor data and vehicle sensor data, pre-processing the multimodal data from different sources to form a public safety event data set; according to the spatiotemporal characteristics of the public safety event data and the relevance analysis results of the data in the public safety event data set, establishing a security event relevance grouping; by associating the data in the data set, it is convenient to deeply understand the connection and influence between different events.

This invention discloses a distributed large model token counting method based on trace linking, relating to the field of large model management technology. The method involves collecting token consumption data from the previous day's data via a distributed cloud large model server, uploading this data to Kafka, and receiving and parsing the token consumption data from Kafka via a large model management center. Data from different nodes is integrated based on the trace ID to form complete request chain data. Following a hierarchical and domain-based approach, the large model management center stores user token consumption data in object storage. Finally, based on business needs, the large model management center displays relevant statistical data of message chains within a filtered region.