earticle

영어

Many important applications have used novelty detection in order to reduce redundant and non-relevant information presented to users of the document retrieval systems. In this study, sentence level information patterns are proposed for enhancing the novelty detection for Arabic text documents. Two models based on sentence level information patterns are suggested and compared; the first one is based on sentence length while the second one is based on opinion patterns. Experimental results have showed that both of the proposed models; Length Adjusted (LA) model and Length and Opinion Adjusted (LOA) model, can significantly improve the performance of novelty detection for Arabic texts, in terms of precision at top ranks. Better results were provided by LA model over LOA model. This shows that the sentence length is more important for enhancing the novelty detection than other suggested sentence level information patterns (e.g. opinion patterns).