TY - JFULL AU - Faaza A and Almarsoomi and James D and O'Shea and Zuhair A and Bandar and Keeley A and Crockett PY - 2012/11/ TI - Arabic Word Semantic Similarity T2 - International Journal of Cognitive and Language Sciences SP - 2496 EP - 2505 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/12864 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 70, 2012 N2 - This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field. ER -