This review discussed the dilemma of small data faced by materials machine learning. First,
we analyzed the limitations brought by small data. Then, the workflow of materials machine …

Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

Abstract Named Entity Recognition (NER), one of the most fundamental problems in natural
language processing, seeks to identify the boundaries and types of entities with specific …

The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

An enormous amount of digital information is expressed as natural-language (NL) text that is
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …

Process of information extraction (IE) is used to extract useful information from unstructured
or semi-structured data. Big data arise new challenges for IE techniques with the rapid …

This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …

With the rapid development of text mining, many studies observe that text generally contains
a variety of implicit information, and it is important to develop techniques for extracting such …

In modern‐day medicine, medical imaging has undergone immense advancements and can
capture several biomedical images from patients. In the wake of this, to assist medical …

Narratives are present in many forms of human expression and can be understood as a
fundamental way of communication between people. Computational understanding of the …