Comparing words, stems, and roots as index terms in an Arabic Information Retrieval System
Journal of the American Society for Information Science
Stemming methodologies over individual query words for an Arabic information retrieval system
Journal of the American Society for Information Science
Improving stemming for Arabic information retrieval: light stemming and co-occurrence analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Current Approaches in Arabic IR: A Survey
ICADL 08 Proceedings of the 11th International Conference on Asian Digital Libraries: Universal and Ubiquitous Access to Information
An accuracy-enhanced light stemmer for arabic text
ACM Transactions on Speech and Language Processing (TSLP)
A real time Named Entity Recognition system for Arabic text mining
Language Resources and Evaluation
A corpus based approach for the automatic creation of arabic broken plural dictionaries
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
| Hi-index | 0.00 |
Due to the high number of inflectional variations of Arabic words, empirical results suggest that stemming is essential for Arabic information retrieval. However, current light stemming algorithms do not extract the correct stem of irregular (so-called broken) plurals, which constitute ~10% of Arabic texts and ~41% of plurals. Although light stemming in particular has led to improvements in information retrieval [5, 6], the effects of broken plurals on the performance of information retrieval systems has not been examined.We propose a light stemmer that incorporates a broken plural recognition component, and evaluate it within the context of information retrieval. Our results show that identifying broken plurals and reducing them to their correct stems does result in a significant improvement in the performance of information retrieval systems.