Terminology extraction is an essential task in domain knowledge acquisition, as well as for
information retrieval. It is also a mandatory first step aimed at building/enriching …

Background Deep sequencing makes it possible to observe low-frequency viral variants and
sub-populations with greater accuracy and sensitivity than ever before. Existing platforms …

Free association among words is a fundamental and ubiquitous memory task. Although
distributed semantics (DS) models can predict the association between pairs of words, and …

Entity Linking (EL) systems aim to automatically map mentions of an entity in text to the
corresponding entity in a Knowledge Graph (KG). Degree of connectivity of an entity in the …

Variations of word associations across different groups of people can provide insights into
people's psychologies and their world views. To capture these variations, we introduce the …

Automatic Term Extraction (ATE) deals with the extraction of terminology from a domain
specific corpus, and has long been an established research area in data and knowledge …

Recent studies suggest that similarity in emotional features and concreteness are critical
cues underlying word association in native speakers. However, the lexical organization of a …

We design a new co-occurrence based word association measure by incorporating the
concept of significant cooccurrence in the popular word association measure Pointwise …

Non-fungible tokens (NFTs) are decentralized digital tokens to represent the unique
ownership of items. Recently, NFTs have been gaining popularity and at the same time …

How words are interrelated in the human mind is a scientific topic on which there is still no
consensus, with different views on how word co-occurrence and semantic relatedness …