Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Arabic topic detection using automatic text summarisation
AU - Koulali, Rim
AU - El-Haj, Mahmoud
AU - Meziane, Abdelouafi
PY - 2013
Y1 - 2013
N2 - With the exponential growth of the online available Arabic documents, classifying and processing large Arabic corpora has became a challenging task. The presence of noisy information embedded in these documents has made it even more difficult to get accurate results when applying a Topic Detection (TD) process. To address this problem, a proper features selection approach is needed to enhance the topic detection accuracy. In this paper, we explore the impact of using automatic summarisation technique along with a feature-selection process to enhance Arabic Topic Detection. In our work we show that using automatic summarisation reduces noisy information and results in a significant enhancement to the topic detection process and therefore increases the performance of our TD system. This was achieved by the ability of our summariser system in reducing documents size to speed up the detection process.
AB - With the exponential growth of the online available Arabic documents, classifying and processing large Arabic corpora has became a challenging task. The presence of noisy information embedded in these documents has made it even more difficult to get accurate results when applying a Topic Detection (TD) process. To address this problem, a proper features selection approach is needed to enhance the topic detection accuracy. In this paper, we explore the impact of using automatic summarisation technique along with a feature-selection process to enhance Arabic Topic Detection. In our work we show that using automatic summarisation reduces noisy information and results in a significant enhancement to the topic detection process and therefore increases the performance of our TD system. This was achieved by the ability of our summariser system in reducing documents size to speed up the detection process.
U2 - 10.1109/AICCSA.2013.6616460
DO - 10.1109/AICCSA.2013.6616460
M3 - Conference contribution/Paper
SP - 1
EP - 4
BT - Computer Systems and Applications (AICCSA), 2013 ACS International Conference on
PB - IEEE Computer Society
ER -