In natural language processing, short-text semantic similarity (STSS) is a very prominent
field. It has a significant impact on a broad range of applications, such as question …

Recently, the revival of the semantic similarity concept has been featured by the rapidly
growing artificial intelligence research fueled by advanced deep learning architectures …

Auto-grading of short answer questions is considered a challenging problem in the
processing of natural language. It requires a system to comprehend the free text answers to …

Text similarity measurement is a link between basic research such as text modeling and
upper-level application research of text potential information. In order to improve the …

Background Semantic textual similarity (STS) measures the degree of relatedness between
sentence pairs. The Open Health Natural Language Processing (OHNLP) Consortium …

The use of social media in crisis informatics has become increasingly popular across a
range of disciplines. Leveraging natural language processing (NLP) techniques enables the …

Semantic textual similarity analysis finds its practical usage in many real-world natural
language processing applications, including clinical and biomedical settings. Many …

The efficiency of information retrieval systems primarily depends on the effective
representation of documents during query processing. This representation is mainly …

Background Peer assessment has played an important role in large‐scale online learning,
as it helps promote the effectiveness of learners' online learning. However, with the …

The field of computational linguistics has been impacting various issues in language
disciplines. The enormous growth of machine learning algorithms and Natural Language …