Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. A. Hefny,
"Applying formal concept analysis for visualizing DNA methylation statusamong breast cancer tumors subtypes",
The 9th IEEE International Computer Engineering Conference (ICENCO 2013) pp. 37 - 42, Cairo, EGYPT -, December 29-30, , 2013.
Tharwat, A. A., I. A. El-Khodary, and A. A. Radwan,
"Applying the Stability Notions of Parametric Programming to Practical Applications",
8th International Conference on Parametric Optimization and Related Topics, PARAOPT VIII, Cairo, Egypt, November, 2005.
Tharwat, A. A., I. A. El-Khodary, and A. A. Radwan,
"Applying the Stability Notions of Parametric Programming to Practical Applications",
8th International Conference on Parametric Optimization and Related Topics, PARAOPT VIII, Cairo, Egypt, November, 2005.
Abstractn/a
Shaalan, K., R. Aref, and A. Fahmy,
"An Approach for Analyzing and Correcting Spelling Errors for Non-native Arabic learners",
The 7th International Conference on Informatics and Systems (INFOS2010), Cairo, Egypt, Faculty of Comptuers and Information, 2010.
AbstractSpell checkers are widely used in many software products for identifying errors in users' writings. However, they are not designed to address spelling errors made by non-native learners of a language. As a matter of fact, spelling errors made by non-native learners are more than just misspellings. Non-native learners' errors require special handling in terms of detection and correction, especially when it comes to morphologically rich languages such as Arabic, which have few related resources. In this paper, we address common error patterns made by non-native Arabic learners and suggest a two-layer spell-checking approach, including spelling error detection and correction. The proposed error detection mechanism is applied on top of Buckwalter's Arabic morphological analyzer in order to demonstrate the capability of our approach in detecting possible spelling errors. The correction mechanism adopts a rule-based edit distance algorithm. Rules are designed in accordance with common spelling error patterns made by Arabic learners. Error correction uses a multiple filtering mechanism to propose final corrections. The approach utilizes semantic information given in exercising questions in order to achieve highly accurate detection and correction of spelling errors made by non-native Arabic learners. Finally, the proposed approach was evaluated using real test data and promising results were achieved.