Online web navigation assistant

N.M. Ali, A.M. Gadallah, H.A. Hefny, B.A. Novikov
<span title="">2021</span> <i title="Udmurt State University"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bib5ilppqzaqnofpoiqpy3v6au" style="color: black;">Vestnik Udmurtskogo Universiteta Matematika Mekhanika Komp yuternye Nauki</a> </i> &nbsp;
The problem of finding relevant data while searching the internet represents a big challenge for web users due to the enormous amounts of available information on the web. These difficulties are related to the well-known problem of information overload. In this work, we propose an online web assistant called OWNA. We developed a fully integrated framework for making recommendations in real-time based on web usage mining techniques. Our work starts with preparing raw data, then extracting useful
more &raquo; ... information that helps build a knowledge base as well as assigns a specific weight for certain factors. The experiments show the advantages of the proposed model against alternative approaches.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35634/vm210109">doi:10.35634/vm210109</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s3rxw3ypxbdh3evupitqvh44xe">fatcat:s3rxw3ypxbdh3evupitqvh44xe</a> </span>
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