Multi-word term indexing for Arabic document retrieval

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.