Recommender System for E-Research.
Subject Area
Computer and Control Systems Engineering
Article Type
Original Study
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.
Recommended Citation
M. Riad, A.; Elminir, Hamdy; and Sabbeh, Sahar
(2021)
"Recommender System for E-Research.,"
Mansoura Engineering Journal: Vol. 33
:
Iss.
1
, Article 2.
Available at:
https://doi.org/10.21608/bfemu.2021.209232