Impact of Term-Indexing for Arabic Document Retrieval

Authors:
Siham Boulaknadel
Affiliations:
LINA FRE CNRS 2729 Université de Nantes, Nantes cedex 03, France 44322 and GSCM Université Mohammed V, Agdal Rabat-Maroc
Venue:
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Year:
2008

Citing 4
Cited 0

Probabilistic methods for searching ocr-degraded arabic text

Probabilistic methods for searching ocr-degraded arabic text
Accurate methods for the statistics of surprise and coincidence

Computational Linguistics - Special issue on using large corpora: I
Word association norms, mutual information, and lexicography

ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Automatic tagging of Arabic text: from raw text to base phrase chunks

HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.