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DOI: 10.14569/IJACSA.2016.071218
PDF

Stemmer Impact on Quranic Mobile Information Retrieval Performance

Author 1: Huda Omar Aljaloud
Author 2: Mohammed Dahab
Author 3: Mahmoud Kamal

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.

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Abstract: Stemming algorithms are employed in information retrieval (IR) to reduce verity variants of the same word with several endings to a standard stem. Stemmers can also help IR systems by unifying vocabulary, reducing term variants, reducing storage space, and increasing the likelihood of matching documents, all of which make stemming very attractive for use in IR. This paper aims to study the impact of using stemming techniques in mobile effectiveness. Two-word extraction stemming techniques will be used: a light stemmer and a dictionary-lookup stemmer. Also, three sets of experiments were conducted in this research in order to raise the efficiency of mobile aapplications. Implementing the two stemming approaches and assessing their accuracy by calculating the precision, recall, MAP, and f-measure, produced results which show that the light10 stemmer outperforms the dictionary-lookup stemmer in precision and MAP. Furthermore, the mobile performance of the light10 stemmer exceeds that of the dictionary-based stemmer.

Keywords: stemming; information retrieval; light10; Quran lexicon; mobile performance; natural language processing

Huda Omar Aljaloud, Mohammed Dahab and Mahmoud Kamal, “Stemmer Impact on Quranic Mobile Information Retrieval Performance” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071218

@article{Aljaloud2016,
title = {Stemmer Impact on Quranic Mobile Information Retrieval Performance},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071218},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071218},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Huda Omar Aljaloud and Mohammed Dahab and Mahmoud Kamal}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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