An Improved Arabic Light Stemmer - Elrajubi, Osama Mohamed
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Stemming as part of Natural Language Processing is very useful in many applications such as information retrieval, data encryption, text compression, text classification and categorization. Arabic stemming becomes mainly important for Arabic Information Retrieval (IR), for the reason that IR has to determine an appropriate form of words as index. Arabic is highly inflected language, therefore there is a need for an efficient stemming algorithm for the retrieval and indexing of Arabic documents.

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Produktbeschreibung
Stemming as part of Natural Language Processing is very useful in many applications such as information retrieval, data encryption, text compression, text classification and categorization. Arabic stemming becomes mainly important for Arabic Information Retrieval (IR), for the reason that IR has to determine an appropriate form of words as index. Arabic is highly inflected language, therefore there is a need for an efficient stemming algorithm for the retrieval and indexing of Arabic documents.
Autorenporträt
Osama Mohamed Elrajubi received the BSc degree in Computer Engineering from the College of Industrial Technology - Misrata, Libya in 2002, and MSc degree in Computer Sciences from the Academy of Postgraduate Studies - Tripoli, Libya in 2009. He also hold an MSc degree in Computer Engineering from Nottingham Trent University-UK.