Authors: Laiali Almazaydeh
Addresses: Faculty of Information Technology, Al-Hussein Bin Talal University, Ma'an, Jordan
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.
Keywords: information retrieval; Arabic language; summarisation; trilateral root; aggregate similarity.
International Journal of Intelligent Systems Technologies and Applications, 2018 Vol.17 No.3, pp.272 - 280
Available online: 10 Aug 2018 *Full-text access for editors Access for subscribers Purchase this article Comment on this article