Stemming and Lemmatization for Information Retrieval Systems in Amazigh Language

Stemming and lemmatization are two language modeling techniques used to improve the document retrieval precision performances. Stemming is a procedure to reduce all words with the same stem to a common form whereas lemmatization removes inflectional endings and returns the base form of a word. The idea of this paper is to explain how a stemming or lemmatization in Amazigh language can improve the search outcomes by providing results that fit better with the query the user introduced. In Document retrieval systems, lemmatization produced better precision compared to stemming. Overall the findings suggest that language modeling techniques improves document retrieval, with lemmatization technique producing the best result.