An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval
This work addresses information retrieval challenges for Arabic language users, representing an incremental improvement in stemming techniques.
The paper tackles the problem of indexing and retrieving Arabic texts by proposing an enhanced stemming algorithm that uses templates to replace words with stems, achieving up to 96% accuracy in root extraction and improving information retrieval results.
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.