ONLINE WEB NAVIGATION ASSISTANT

被引：4

作者：

Ali, N. M. ^{[1
,2
]}

Gadallah, A. M. ^{[3
]}

Hefny, H. A. ^{[1
]}

Novikov, B. A. ^{[4
]}

机构：

[1] St Petersburg State Univ, Dept Comp Sci, Fac Math & Mech, St Petersburg, Russia

[2] Port Said Univ, Port Said, Egypt

[3] Cairo Univ, Fac Grad Studies Stat Res, Dept Comp Sci, Giza, Egypt

[4] Natl Res Univ Higher Sch Econ, Dept Informat, St Petersburg, Russia

来源：

VESTNIK UDMURTSKOGO UNIVERSITETA-MATEMATIKA MEKHANIKA KOMPYUTERNYE NAUKI | 2021年 / 31卷 / 01期

关键词：

web mining; web personalization; link prediction; web usage mining; recommender systems; web log; web navigation assistant; RECOMMENDATION;

D O I：

10.35634/vm210109

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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.

引用

页码：116 / 131

页数：16

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