  The effectiveness of three stop words lists for Arabic Information
Retrieval---General Stoplist, Corpus-Based Stoplist, Combined Stoplist ---were
investigated in this study. Three popular weighting schemes were examined: the
inverse document frequency weight, probabilistic weighting, and statistical
language modelling. The Idea is to combine the statistical approaches with
linguistic approaches to reach an optimal performance, and compare their effect
on retrieval. The LDC (Linguistic Data Consortium) Arabic Newswire data set was
used with the Lemur Toolkit. The Best Match weighting scheme used in the Okapi
retrieval system had the best overall performance of the three weighting
algorithms used in the study, stoplists improved retrieval effectiveness
especially when used with the BM25 weight. The overall performance of a general
stoplist was better than the other two lists.
