Given the emergence of data science and machine learning throughout all aspects of
society, but particularly in the scientific domain, there is increased importance placed on …

Valuable knowledge of catalysis is often hidden in a large amount of scientific literature.
There is an urgent need to extract useful knowledge to facilitate scientific discovery. This …

命名实体识别技术是信息抽取, 机器翻译, 问答系统等多种自然语言处理技术中一项重要的基本
任务. 近年来, 基于深度学习的命名实体识别技术成为一大研究热点. 为了方便研究者们了解基于 …

Purpose The majority of existing studies about named entity recognition (NER) concentrate
on the prediction enhancement of deep neural network (DNN)-based models themselves …

Annotated corpora are indispensable tools to train computational models in Natural
Language Processing. However, in the case of more complex semantic annotation …

The application of machine learning to the materials domain has traditionally struggled with
two major challenges: a lack of large, curated data sets and the need to understand the …

The inconsistency of polymer indexing caused by the lack of uniformity in expression of
polymer names is a major challenge for widespread use of polymer related data resources …

This paper presents an active learning approach that aims to reduce the human effort
required during the annotation of natural language corpora composed of entities and …

In response to the escalating demand for robust security solutions in increasingly complex
Internet of Things (IoT) networks, this study introduces an advanced Intrusion Detection …

Researchers worldwide are seeking to repurpose existing drugs or discover new drugs to
counter the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS …