Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a
given document. Recently, researchers have conducted in-depth studies on this task from …

The keyphrases of a document are the textual units that characterize its content such as the
topics it addresses, its ideas, their field, etc. Thousands of books, articles and web pages are …

In the evolution of the Internet, social media platform like Twitter has permitted the public
user to share information such as famous current affairs, events, opinions, news, and …

Due to the exponential growth of online information, the ability to efficiently extract the most
informative content and target specific information without extensive reading is becoming …

The extraction of keywords is a critical task in natural language processing and information
retrieval. It has become increasingly important in a wide range of applications, from search …

Keyword extraction by Term frequency‐Inverse document frequency (TF‐IDF) is used for text
information retrieval and mining in many domains, such as news text, social contact text, and …

With growing amounts of available textual data, development of algorithms capable of
automatic analysis, categorization, and summarization of these data has become a …

Background: Keyword extraction is a popular research topic in the field of natural language
processing. Keywords are terms that describe the most relevant information in a document …

Dynamic data-driven vulnerability assessments face massive heterogeneous data contained
in, and produced by SOCs (Security Operations Centres). Manual vulnerability assessment …