Kotevski, Aleksandar and Martinovska Bande, Cveta (2014) Improved algorithm for tag-based collaborative filtering. A Journal for Information Technology, Education Development and Teaching Methods of Technical and Natural Sciences, 4 (1). pp. 1-7. ISSN ISSN 2217-7949
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Abstract
Important aspect in the modern e-learning
systems is selecting the most adequate learning materials
based on learners’ requirements, needs and knowledge
goals. Recommender systems based on collaborative
filtering contribute to overcoming the information
overload in personalized learning environments. That’s
why there is imminent need of using systems that have the
capability to detect the learners’ needs and to recommend
them the most adequate learning context. In recent years,
it is common practice to use tags in the process of filtering
the most useful learning materials.Through the tagging,
learners can mark or highlight some learning materials
and can contribute to organizing and retrieving useful
learning materials.
Our previous researches were focused on tag-based
collaborative filtering and learning style determination,
the factors that affect the tag-based collaborative filtering,
in order to suggest useful learning material in adequate
format.
In this paper, we propose a new tag-based collaborative
algorithm that takes in consideration the factors that
affect the tag-based collaborative filtering in order to
develop more efficient and accurate algorithm, and
suggest the learning materials based on posted tags rating
and students rating.
The developed system was implemented at the Faculty of
Law – Bitola, and the evaluation results are shown in this
paper.
| Item Type: | Article |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Cveta Martinovska Bande |
| Date Deposited: | 15 May 2017 08:54 |
| Last Modified: | 15 May 2017 08:54 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/17759 |
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