Supervised Learning to Measure the Semantic Similarity Between Arabic Sentences

Many methods for measuring the semantic similarity between sentences have been proposed, particularly for English. These methods are considered restrictive as they usually do not take into account some semantic and syntactic-semantic knowledge like semantic predicate, thematic role and semantic class. Measuring the semantic similarity between sentences in Arabic is particularly a challenging task because of the complex linguistic structure of the Arabic language and given the lack of electronic resources such as syntactic-semantic knowledge and annotated corpora.