Title :
A Triliteral Word Roots Extraction Using Neural Network For Arabic
Author :
Al-Serhan, Hasan ; Ayesh, Aladdin
Author_Institution :
Sch. of Comput., De Montfort Univ., Leicester
Abstract :
Many of existing Arabic stemming algorithms use a large set of rules. In many cases, they refer to a lookup table of patterns and roots. This requires a large storage space, and time to access the information. A novel neural network based approach for stemming Arabic words is proposed in this paper. This approach attempts to exploit numerical relations between characters by using backpropagation neural network (BPNN). No such system in literature can be found that uses neural network to extract the stemming of Arabic words
Keywords :
backpropagation; natural language processing; neural nets; Arabic language; Arabic stemming algorithm; Arabic word stemming; backpropagation neural network; natural language processing; triliteral word roots extraction; Backpropagation; Computational intelligence; Computer networks; Data mining; Joining processes; Natural language processing; Natural languages; Neural networks; Radiofrequency interference; Table lookup; Arabic Language; Backpropagation; Natural Language Processing; Neural Networks; Stemming;
Conference_Titel :
Computer Engineering and Systems, The 2006 International Conference on
Conference_Location :
Cairo
Print_ISBN :
1-4244-0271-9
Electronic_ISBN :
1-4244-0272-7
DOI :
10.1109/ICCES.2006.320487