Artificial Intelligence federates numerous scientific fields in the aim of developing machines
able to assist human operators performing complex treatments---most of which demand high …

Abstract Objective Systematic Reviews (SRs) are utilized to summarize evidence from high
quality studies and are considered the preferred source of evidence-based practice (EBP) …

In bioinformatics, semantic similarity has been used to compare different types of biomedical
entities, such as proteins, compounds and phenotypes, based on their biological role …

This paper introduces a new family of intrinsic and corpus-based Information Content (IC)
models for ontology-based similarity measures based on the IC theory, a detailed state of …

Semantic similarity and relatedness computation has attracted an increasing amount of
attention among researchers. The majority of previous studies, including edge-based and …

Behavioral targeting is a technique extensively used by the advertising industry that consists
on compiling the interests of the individuals that surf the web by tracking the web sites they …

The rapid growth in the digital era initiates the need to inculcate and preserve the academic
originality of translated texts. Cross-lingual semantic similarity is concerned with identifying …

The determination of semantic similarity between word pairs is an important task in text
understanding that supports the processing, classification and structuring of textual …

Noise addition is a data distortion technique widely used in data intensive applications. For
example, in machine learning tasks it helps to reduce overfitting, whereas in data privacy …

Computing the semantic similarity between pairs of terms plays a vital role within a myriad of
shared data applications, such as data integration and ontology evolution. A first step …