Automatic Arabic text summarisation system (AATSS) based on morphological analysis

Abstract

The automatic text summarisation is a challenging task. Existing techniques suffer from inadequate investigation for Arabic text. The majority of Arabic words are derived according to the morphology that is more complicated than English and other natural languages. The approach reported in this paper elaborates a morphological analysis to develop a new automatic Arabic text summarisation. The proposed approach is based on three main phases: the text tokenization phase, the trilateral root extraction phase and the aggregate similarity computation phase. The proposed approach has been extensively experimented on samples from the benchmark datasets of Essex Arabic summaries corpus (EASC). Experimental results show the ability of the proposed system to extract relevant sentences that reflects the summary of Arabic text, as well as a comparable performance with other reported techniques in the literature.