International Journal of Information and Communication Technology Research
مجله بین المللی ارتباطات و فناوری اطلاعات
International Journal of Information and Communication Technology Research
Engineering & Technology
http://ijict.itrc.ac.ir
1
admin
2251-6107
2783-4425
doi
1652
25391
en
jalali
1395
3
1
gregorian
2016
6
1
8
2
online
1
fulltext
fa
A New Hybrid Collaborative Recommender Using Semantic Web Technology and Demographic data
فناوری اطلاعات
Information Technology
پژوهشي
Research
Recommender systems are gaining a great importance with the emergence of E-commerce and business on the internet. Collaborative Filtering (CF) is one of the most promising techniques in recommender systems. It uses the known preferences of a group of users to make recommendations for other users. Regardless of its success in many application domains, CF has main limitations such as sparsity, scalability and new user/item problems. As new direction, semantic-based recommenders have emerged that deal with the semantic information of items. Such systems can improve the performance of classical CF by allowing the recommender system to make inferences based on an additional source of knowledge. Moreover, the incorporation of demographic data in recommender systems can help to improve the quality of recommendations. In this paper, we present a new hybrid CF approach that exploits Semantic Web Technology as well as demographic data to alleviate all the problems mentioned above. The experimental results on the MovieLens dataset verify the effectiveness and efficiency of our approach over other benchmarks.
recommender system, collaborative filtering, semantic Web, demographic data, e-commerce
51
61
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-48&slc_lang=fa&sid=1
Faezeh Sadat
Gohari
1003194753284600148
1003194753284600148
Yes
Mohammad Jafar
Tarokh
1003194753284600149
1003194753284600149
No