A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

Recent advances in relation extraction with deep neural architectures have achieved
excellent performance. However, current models still suffer from two main drawbacks: 1) …

Natural language processing (NLP) may face the inexplicable “black-box” problem of
parameters and unreasonable modeling for lack of embedding of some characteristics of …

The existing traffic parameter prediction methods generally adopt a single prediction model,
but the fusion of different theories and methods can complement each other and improve the …

Meta-learning has recently promoted few-shot text classification, which identifies target
classes based on information transferred from source classes through a series of small tasks …

In recent years, due to the rapid development of social media, there have been many
propaganda texts and propaganda activities on the internet. While previous studies have …

Summarization generates a brief and concise summary which portrays the main idea of the
source text. There are two forms of summarization: abstractive and extractive. Extractive …

Multiple tasks within the field of geographical information retrieval and geographical
information sciences necessitate toponym matching, which involves the challenge of …

Re-ranking is to refine the candidate ranking list of recommended items, such that the re-
ranked list attracts users to purchase or click more items than the candidate one without re …

Deep learning (DL) models have significantly improved the performance of text classification
and text regression tasks. However, DL models are often strikingly vulnerable to adversarial …