Research output: Contribution to journal › Article › peer-review
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 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.
Original language | English |
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Pages (from-to) | 116-131 |
Number of pages | 16 |
Journal | Vestnik Udmurtskogo Universiteta: Matematika, Mekhanika, Komp'yuternye Nauki |
Volume | 31 |
Issue number | 1 |
DOIs | |
State | Published - 1 Mar 2021 |
ID: 76923713