Struggling with microseismic signal classification in deep underground engineering? Researchers from Sichuan University ...

We have all been there. You are sitting around with friends, maybe after a couple of drinks, and someone says, “You know what would make a great app?” You get excited, you brainstorm features, you ...

The successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning.

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Abstract: News text classification is crucial for efficient information acquisition and dissemination. While deep learning models, such as BERT and BiGRU, excel in accuracy for text classification, ...

Abstract: Multi-label text classification involves assigning multiple relevant categories to a single text, enabling applications in academic indexing, medical diagnostics, and e-commerce. However, ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...

In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...