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

页码：480 / +

页数：3

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