Semantic similarity between different texts is a challenging task. It measures the relation
between texts, sentences and words to depict their degree of similarity or resemblance …

Semantic Textual Similarity (STS) is the task of identifying the semantic correlation between
two sentences of the same or different languages. STS is an important task in natural …

Semantic similarity is the task of measuring relations between sentences or words to
determine the degree of similarity or resemblance. Several applications of natural language …

Big-data is one of the milestones on the web especially on social media (SM). Due to the
widespread popularity of SM on the web, it is a painful task to capture the essence of SM. In …

Semantic similarity analysis in natural language texts is getting great attention recently.
Semantic analysis of the Quran is especially challenging because it is not simply factual but …

Word embeddings is the representation of the text using vectors such that the words that
have similar syntax and semantic will have similar vector representation. Representing …

Word embedding has opened new and exciting avenues for understanding and processing
languages. The simple yet effective word embedding models rapidly became a dominant …

Given the lack of Arabic dialect text corpora in comparison with what is available for dialects
of English and other languages, there is a need to create dialect text corpora for use in …

Paraphrase is the act of reusing original texts without proper citation of the source. Different
obfuscation operations can be employed such as addition/deletion of words, synonym …

The similarity between two sentences is the score that represents the relatedness and
likelihood between those sentences. Measuring sentence similarity has attracted …