E-commerce has witnessed remarkable growth, especially following the easing of COVID-19
restrictions. Many people, who were initially hesitant about online shopping, have now …

Effective management and analysis of large-scale textual data presents significant
challenges, notably due to high storage and processing demands. Text regression analysis …

This research delves into the latest advancements in Natural Language Processing (NLP)
and their broader implications, challenges, and future directions. With the ever-increasing …

Support vector machine (SVM) is widely utilized for classification in diverse fields thanks to
its superior performance. However, when tackling large-scale SVM problems, it encounters …

Text processing tasks commonly grapple with the challenge of high dimensionality. One of
the most effective solutions to this challenge is to preprocess text data through feature …

Few-shot intent detection is a more challenging application. However, traditional prototypical
networks based on averaging often suffer from issues such as missing key information, poor …

Anaerobic digestion holds promise as a method for removing antibiotic resistance genes
(ARGs) from dairy waste. However, accurately predicting the efficiency of ARG removal …

The adulteration of camellia seed oil with different processes will seriously violate the rights
and interests of consumers. The accurate identification of camellia seed oil processes is of …

Abstract Machine Learning (ML) is an advanced technology that empowers systems to
acquire knowledge autonomously, eliminating the need for explicit programming. The …

Few-shot text classification (FSTC) strives to predict classes not involved in the training by
learning from a few labeled examples. Currently, most tasks construct meta-tasks in a …