| tech,4-1-P03-1050,ak | users </term> . This paper presents an <term> | unsupervised learning approach | </term> to building a <term> non-English ( | #4436 This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. | |
| tech,6-2-P03-1050,ak | <term> stemming model </term> is based on <term> | statistical machine translation | </term> and it uses an <term> English stemmer | #4454 The stemming model is based on statistical machine translation and it uses an English stemmer and a small (10K sentences) parallel corpus as its sole training resources. | |
| tech,3-7-P03-1050,ak | Task-based evaluation </term> using <term> | Arabic information retrieval | </term> indicates an improvement of 22-38 | #4574 Task-based evaluation using Arabic information retrieval indicates an improvement of 22-38% in average precision over unstemmed text, and 96% of the performance of the proprietary stemmer above. |
