T-Stem--a Superior Stemmer and Temporal Extractor for Arabic Texts‪.‬

ABSTRACT: Stemming has a large effect on Arabic information indexing and retrieval, at least partially due to the highly inflected nature of the language. Our work demonstrates the process of improving other stemmers, mainly that of [1]. We reached a recall difference of 28% over the work of [1]. The main part of improvement was due to the addition of more grammatical rules that facilitate the process of stemming. Following this part, we implemented a procedure that extracts the temporal references from the texts. This procedure is highly dependable on the stemming process. A list of all the temporal references is used. The type of the temporal word decides the procedure to treat this word and gives the importance of this temporal reference. These conditions, with the help of the stemmer, produced an excellent result of 95% precision rate and of 91% recall rate. Categories and Subject Descriptors