Arabic Text Classification Using N-Gram Frequency Statistics A Comparative Study

This paper presents the results of classifying Arabic text documents using the N-gram frequency statistics technique employing a dissimilarity measure called the "Manhattan distance", and Dice's measure of similarity. The Dice measure was used for comparison purposes. Results show that N-gram text classification using the Dice measure outperforms classification using the Manhattan measure.

• Type: Conference
• Year: 2006
• Where: DMIN
• Authors: Laila Khreisat
• Keywords: Dice Measure, Dice's Measure, DMIN 2006, DMIN 2007, Measure Outperforms Classification