Should one use term proximity or multi-word terms for Arabic information retrieval?

Abstract

Recently, several information retrieval (IR) models have been proposed in order to boost the retrieval performance using term dependencies. However, in the context of the Arabic language, most IR researchers have focused on the problem of stemming, which is highly challenging in this language. In this paper, we propose to explore whether term dependencies can help improve Arabic IR systems, and what are the best methods to use. To do so, we consider both explicit term dependencies based on multi-word terms (MWTs) that are extracted using syntactic patterns and statistical filters, as well as implicit ones based on the notion of cross-terms or term proximities. Our experiments, performed on standard TREC Arabic IR collections, show the importance of taking into account term dependencies for Arabic IR. To the best of our knowledge, this is the first study that provides complete extensions, and their comparison, of most standard IR models to deal with term dependencies in the Arabic language.