Abstract: This paper describes an RAX System designed for ranking Arabic documents in information retrieval processes. The proposed solution basically depends on the similarity of textual content. The model we have designed can be used for documents stored in the different formats and written in Arabic language. Due the complex lingual semantics of this language the proposed solution uses a pure statistical approach. The design and implementation are based on existing text processing frameworks and referent Arabic grammar. The main focus of our research has been the evaluation of different similarity measures used for classifying Arabic documents from different domains and different document categories based on query criteria provided by the user.

Hesham Elzentani, Mladen Veinovic and Goran Šimic, “RAX System to Rank Arabic XML Documents” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071224

@article{Elzentani2016,
title = {RAX System to Rank Arabic XML Documents},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071224},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071224},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Hesham Elzentani and Mladen Veinovic and Goran Šimic}
}