Effects of Stop Words Elimination for Arabic Information Retrieval: A Comparative Study
February 07, 2017 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Ibrahim Abu El-Khair
arXiv ID
1702.01925
Category
cs.CL: Computation & Language
Cross-listed
cs.IR
Citations
111
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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