JOURNAL ARTICLE

AN ACCURACY-ENHANCED STEMMING ALGORITHM FOR ARABIC INFORMATION RETRIEVAL

Sadik BessouMohamed Touahria

Year: 2014 Journal:   Neural Network World Vol: 24 (2)Pages: 117-128   Publisher: Czech Technical University in Prague

Abstract

This paper provides a method for indexing and retrieving Arabic texts, based on natural language processing. Our approach exploits the notion of template in word stemming and replaces the words by their stems. This technique has proven to be effective since it has returned significant relevant retrieval results by decreasing silence during the retrieval phase. Series of experiments have been conducted to test the performance of the proposed algorithm ESAIR (Enhanced Stemmer for Arabic Information Retrieval). The results obtained indicate that the algorithm extracts the exact root with an accuracy rate up to 96% and hence, improving information retrieval.

Keywords:
Computer science Renewable energy Term (time) Numerical weather prediction Industrial engineering Machine learning Data science Meteorology Algorithm Artificial intelligence Engineering

Metrics

6
Cited By
0.00
FWCI (Field Weighted Citation Impact)
19
Refs
0.29
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Biomedical Text Mining and Ontologies
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

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