Multi-word term indexing for Arabic document retrieval

被引：0
|
作者：
Boulaknadel, Siham [1 ]
Daille, Beatrice [1 ]
Driss, Aboutajdine [2 ]
机构：
[1] Univ Nantes, CNRS, FRE 2729, LINA, 2 Rue Houssinire,BP 92208, F-44322 Nantes 03, France
[2] Mohammed V Univ, GSCM, Rabat, Morocco
来源：
2008 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS, VOLS 1-3 | 2008年
关键词：
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
To improve information retrieval system performances, it seems important to identify key phrases which constitute a better representation of text semantic content than single word terms. In this paper, we adapt the standard method for multi-word term extraction for Arabic language. We define the linguistic specifications and develop a term extraction tool. We experiment the term extraction program for document retrieval in a specific domain, evaluate two kinds of multi-word term weighting functions considering either the corpus or the document, and demonstrate the efficiency of multi-word term indexing for both weighting up to 5.8% of average precision.
引用
收藏
页码：480 / +
页数：3
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