Paraphrasing identification Using ACV-tree kernel
Marwah Alian · Procedia Computer Science · 2024
The aim of paraphrasing identification techniques is to identify if two sentences or texts have the same meaning; even if they do not contain a number of identical phrases or words. In this paper we proposed a hybrid technique based on using attention constituency vector (ACV)-tree kernel in short texts or sentence similarity computation. Then a similarity threshold is used to identifying if these sentences are paraphrased or not. The experiments are conducted on Arabic paraphrasing benchmark. The proposed method provides a recall of 70% and a precision of 76%, when the determined threshold is 0.5, while a recall of 94% and a precision of 0.751 achieved using a threshold of 0.3.