Online Web Navigation Assistant

No'aman Muhammad Ali, Ahmed Mohamed Gadallah, Hesham Ahmed Hefny, Boris Asenovich Novikov

Research output: Contribution to journalArticlepeer-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 languageEnglish
Pages (from-to)116-131
Number of pages16
JournalVestnik Udmurtskogo Universiteta: Matematika, Mekhanika, Komp'yuternye Nauki
Issue number1
StatePublished - 2021

Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)
  • Fluid Flow and Transfer Processes


  • Link prediction
  • Recommender systems
  • Web log
  • Web mining
  • Web navigation assistant
  • Web personalization
  • Web usage mining


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