Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...

Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...

The Jets are learning different ways to get the job done. After an 0-7 start that included 5 one-score losses, the Jets have flipped the script since Week 8. Sunday's victory over the Atlanta Falcons ...

What if you could build an autonomous system that not only executes complex, long-running tasks but also adapts to evolving challenges with remarkable precision? Enter Deep Agents, a innovative ...

All of modern mathematics is built on the foundation of set theory, the study of how to organize abstract collections of objects. But in general, research mathematicians don’t need to think about it ...

Ian Gillan's says growing vision problems could mean retirement from Deep Purple is "not far off." Now 80, Gillan is still performing with the group he joined in 1969, completing a huge tour late last ...

Gene regulatory network (GRN) inference is a central task in systems biology. However, due to the noisy nature of gene expression data and the diversity of regulatory structures, accurate GRN ...