| other,16-7-P03-1050,ak | <term> average precision </term> over <term> | unstemmed text | </term> , and 96 % of the performance of | #4587 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. | |
| tech,34-6-P03-1050,ak | annotated text </term> , in addition to an <term> | unsupervised component | </term> . <term> Task-based evaluation </term> | #4568 Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component . | |
| tech,13-2-P03-1050,ak | translation </term> and it uses an <term> | English stemmer | </term> and a <term> small ( 10K sentences | #4461 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,16-6-P03-1050,ak | a state of the art , proprietary <term> | Arabic stemmer | </term> built using <term> rules </term> , <term> | #4550 Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. | |
| measure(ment),13-7-P03-1050,ak | indicates an improvement of 22-38 % in <term> | average precision | </term> over <term> unstemmed text </term> , | #4584 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. | |
| tech,1-6-P03-1050,ak | needs <term> affix removal </term> . Our <term> | resource-frugal approach | </term> results in 87.5 % <term> agreement | #4535 Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. | |
| tech,0-7-P03-1050,ak | <term> unsupervised component </term> . <term> | Task-based evaluation | </term> using <term> Arabic information retrieval | #4571 Our resource-frugal approach results in 87.5% agreement with a state of the art, proprietary Arabic stemmer built using rules, affix lists, and human annotated text, in addition to an unsupervised component. 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. |
