@article{MAKHILLIJSC201611621363,
    title = {An Automatic Arabic Web Personalization Search Engines and Information Retrieval Systems},
    journal = {International Journal of Soft Computing},
    volume = {11},
    number = {6},
    pages = {382-390},
    year = {2016},
    issn = {1816-9503},
    doi = {ijscomp.2016.382.390},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2016.382.390},
    author = {Safaa I.,Rasha M.,Nagwa L. and},
    keywords = {Information Retrieval (IR),personalized search engines,automatic user profile,machine learning,semantic web ranking,ontology,Web Ontology Language (OWL),personalized information,retrieval,collaborative filtering,contextual-based personalization,arabic language},
    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.}
    }