EN
TR
New prediction methods for collaborative filtering
Abstract
Companies, in particular e-commerce companies, aims to increase customer satisfaction, hence in turn increase their profits, using recommender systems. Recommender Systems are widely used nowadays and they provide strategic advantages to the companies that use them. These systems consist of different stages. In the first stage, the similarities between the active user and other users are computed using the user-product ratings matrix. Then, the neighbors of the active user are found from these similarities. In prediction calculation stage, the similarities computed at the first stage are used to generate the weight vector of the closer neighbors. Neighbors affect the prediction value by the corresponding value of the weight vector. In this study, we developed two new methods for the prediction calculation stage which is the last stage of collaborative filtering. The performance of these methods are measured with evaluation metrics used in the literature and compared with other studies in this field.
Keywords
Details
Primary Language
English
Subjects
-
Journal Section
-
Publication Date
May 1, 2016
Submission Date
May 2, 2016
Acceptance Date
-
Published in Issue
Year 2016 Volume: 22 Number: 2
APA
Bulut, H., & Milli, M. (2016). New prediction methods for collaborative filtering. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 22(2), 123-128. https://izlik.org/JA55FA87EM
AMA
1.Bulut H, Milli M. New prediction methods for collaborative filtering. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2016;22(2):123-128. https://izlik.org/JA55FA87EM
Chicago
Bulut, Hasan, and Musa Milli. 2016. “New Prediction Methods for Collaborative Filtering”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22 (2): 123-28. https://izlik.org/JA55FA87EM.
EndNote
Bulut H, Milli M (May 1, 2016) New prediction methods for collaborative filtering. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22 2 123–128.
IEEE
[1]H. Bulut and M. Milli, “New prediction methods for collaborative filtering”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 22, no. 2, pp. 123–128, May 2016, [Online]. Available: https://izlik.org/JA55FA87EM
ISNAD
Bulut, Hasan - Milli, Musa. “New Prediction Methods for Collaborative Filtering”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 22/2 (May 1, 2016): 123-128. https://izlik.org/JA55FA87EM.
JAMA
1.Bulut H, Milli M. New prediction methods for collaborative filtering. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2016;22:123–128.
MLA
Bulut, Hasan, and Musa Milli. “New Prediction Methods for Collaborative Filtering”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 22, no. 2, May 2016, pp. 123-8, https://izlik.org/JA55FA87EM.
Vancouver
1.Hasan Bulut, Musa Milli. New prediction methods for collaborative filtering. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi [Internet]. 2016 May 1;22(2):123-8. Available from: https://izlik.org/JA55FA87EM
