Abstract: Over the years, several achievements on the improvement of web personalized searching based on user’s interests, preferences and contextual information have been made, unfortunately, most of them are concerned with the static profile approach, preferences or weight values and not changed once the user preference profile is created and this might be unacceptable by users. Also, they didn’t consider usage features like the changing in user’s attributes, ontology, description and features over time. In addition, its rare that any of them are considered in Arabic Language Personalization Re-ranking through the search engines. Therefore, in this study we proposed a New Automatic Semantic Personalization Re-ranking (NASPR) approach. The objective of this NASPR algorithm is to overcome the drawbacks of ranking algorithms and improve the efficiency of web searching. The NASPR approach was applied to 242 Arabic Corpus to measure its performance and the results show improvements in the recall and precision by using the new personalized approach.