Capturing out-of-vocabulary words in Arabic text
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A novel approach to the extraction of roots from Arabic words using bigrams
Journal of the American Society for Information Science and Technology
A comparison study of some Arabic root finding algorithms
Journal of the American Society for Information Science and Technology
An accuracy-enhanced light stemmer for arabic text
ACM Transactions on Speech and Language Processing (TSLP)
Benchmarking and assessing the performance of Arabic stemmers
Journal of Information Science
An application of neural network for extracting Arabic word roots
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Arabic texts analysis for topic modeling evaluation
Information Retrieval
A malay stemmer for jawi characters
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Effect of ISRI stemming on similarity measure for arabic document clustering
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
A plagiarism detection system for arabic text-based documents
PAISI'12 Proceedings of the 2012 Pacific Asia conference on Intelligence and Security Informatics
The Effect of Stemming on Arabic Text Classification: An Empirical Study
International Journal of Information Retrieval Research
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We have implemented a root-extraction stemmer for Arabic which is similar to the Khoja stemmer but without a root dictionary. Our stemmer was found to perform equivalently to the Khoja stemmer as well as so-called llightm stemmers in monolingual document retrieval tasks performed on the Arabic Trec-2001 collection. A root dictionary, therefore, does not improve Arabic monolingual document retrieval.