Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Online Web Navigation Assistant. / Ali, No'aman Muhammad; Gadallah, Ahmed Mohamed; Hefny, Hesham Ahmed; Novikov, Boris Asenovich.
в: Vestnik Udmurtskogo Universiteta: Matematika, Mekhanika, Komp'yuternye Nauki, Том 31, № 1, 01.03.2021, стр. 116-131.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Online Web Navigation Assistant
AU - Ali, No'aman Muhammad
AU - Gadallah, Ahmed Mohamed
AU - Hefny, Hesham Ahmed
AU - Novikov, Boris Asenovich
N1 - Publisher Copyright: © 2021 Udmurt State University. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - 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.
AB - 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.
KW - Link prediction
KW - Recommender systems
KW - Web log
KW - Web mining
KW - Web navigation assistant
KW - Web personalization
KW - Web usage mining
UR - http://www.scopus.com/inward/record.url?scp=85105478346&partnerID=8YFLogxK
U2 - 10.35634/VM210109
DO - 10.35634/VM210109
M3 - Article
AN - SCOPUS:85105478346
VL - 31
SP - 116
EP - 131
JO - ВЕСТНИК УДМУРТСКОГО УНИВЕРСИТЕТА. МАТЕМАТИКА. МЕХАНИКА. КОМПЬЮТЕРНЫЕ НАУКИ
JF - ВЕСТНИК УДМУРТСКОГО УНИВЕРСИТЕТА. МАТЕМАТИКА. МЕХАНИКА. КОМПЬЮТЕРНЫЕ НАУКИ
SN - 1994-9197
IS - 1
ER -
ID: 76923713