| other,12-3-P03-1051,bq | </term> to determine the most probable <term> | morpheme sequence | </term> for a given <term> input </term> . The | #4682 The algorithm uses a trigram language model to determine the most probable morpheme sequence for a given input. |
| model,1-4-P03-1051,bq | for a given <term> input </term> . The <term> | language model | </term> is initially estimated from a small | #4690 The language model is initially estimated from a small manually segmented corpus of about 110,000 words. |
| lr,34-5-P03-1051,bq | expanded <term> vocabulary </term> and <term> | training corpus | </term> . The resulting <term> Arabic word | #4740 To improve the segmentation accuracy, we use an unsupervised algorithm for automatically acquiring new stems from a 155 million word unsegmented corpus, and re-estimate the model parameters with the expanded vocabulary and training corpus . |
| lr,15-6-P03-1051,bq | <term> exact match accuracy </term> on a <term> | test corpus | </term> containing 28,449 <term> word tokens | #4758 The resulting Arabic word segmentation system achieves around 97% exact match accuracy on a test corpus containing 28,449 word tokens. |
