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209232

Recommender System for E-Research.

Article

Last updated: 22 Jan 2023

OverviewSimilar Items

Subjects

-

Tags

Computer Engineering and Systems

Abstract

The typical architecture of the recommender systems consists of two components performed offline and online with respect to the Web server activity. The offline component includes the Preprocessing and Pattern Discovery phases, while the online one implements the Pattern Analysis phase to generate recommendations such as links to pages, advertisements, or information relating to products or services estimated to be of interest for the current user.
This paper presents an online web-based recommender system that collapses the offline and online modules of the typical recommender system into a single module. The proposed system can adapt itself not only to its users, but also to the open Web having the ability to find relevant content on the web. Also, it has the ability to personalize and adapt this content based on the system's observation of its learners. Although learners do not have direct interaction with the open Web, the system can retrieve relevant papers from a paper from a paper list database on remote site such as cite seer or Google Scholar so that, the system can adapt to the open web as well as adapting itself to its users.

DOI

10.21608/bfemu.2021.209232

Authors

First Name

A.

Last Name

M. Riad

MiddleName

-

Affiliation

Head of Information System Department, Faculty of Computers and Information Sciences, Mansoura University, Mansoura, Egypt

Email

amriad2000@yahoo.com

City

Mansoura

Orcid

-

First Name

Hamdy

Last Name

Elminir

MiddleName

K.

Affiliation

National Research Institute of Astronomy of Solar and Space Research, El-marsad Street P.O. box 11421 Helwan, Cairo, Egypt.

Email

hamdy_elminir@hotmail.com

City

Cairo

Orcid

-

First Name

Sahar

Last Name

Sabbeh

MiddleName

F.

Affiliation

Alzarka Higher institute for administration & computer sciences

Email

m_sabbeh@yahoo.com

City

-

Orcid

-

Volume

33

Article Issue

1

Related Issue

18956

Issue Date

2008-03-01

Receive Date

2008-01-01

Publish Date

2021-12-01

Page Start

1

Page End

10

Print ISSN

1110-0923

Online ISSN

2735-4202

Link

https://bfemu.journals.ekb.eg/article_209232.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=209232

Order

2

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023