Dynamic k Neighbor Selection for Collaborative Filtering

Halil Zeybek; Cihan Kaleli

doi:10.18038/aubtda.346407

EN

Dynamic k Neighbor Selection for Collaborative Filtering

Abstract

Collaborative filtering is a commonly used method to reduce information overload. It is widely used in recommendation systems due to its simplicity. In traditional collaborative filtering, recommendations are produced based on similarities among users/items. In this approach, the most correlated k neighbors are determined, and a prediction is computed for each user/item by utilizing this neighborhood. During recommendation process, a predefined k value as a number of neighbors is used for prediction processes. In this paper, we analyze the effect of selecting different k values for each user or item. For this purpose, we generate a model that determines k values for each user or item at the off-line time. Empirical outcomes show that using the dynamic k values during the k-nn algorithm leads to more favorable recommendations compared to a constant k value.

Keywords

k-nearest-neighbor; Collaborative filtering; Dynamic k; Accuracy.

References

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Halil Zeybek This is me
Türkiye

Cihan Kaleli
Türkiye

Publication Date

March 31, 2018

Submission Date

October 25, 2017

Acceptance Date

February 19, 2018

Published in Issue

Year 2018 Volume: 19 Number: 2

DOI

https://doi.org/10.18038/aubtda.346407

IZ

https://izlik.org/JA98GJ72ZD

APA

Zeybek, H., & Kaleli, C. (2018). Dynamic k Neighbor Selection for Collaborative Filtering. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, 19(2), 303-315. https://doi.org/10.18038/aubtda.346407

AMA

1.Zeybek H, Kaleli C. Dynamic k Neighbor Selection for Collaborative Filtering. AUJST-A. 2018;19(2):303-315. doi:10.18038/aubtda.346407

Chicago

Zeybek, Halil, and Cihan Kaleli. 2018. “Dynamic K Neighbor Selection for Collaborative Filtering”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 19 (2): 303-15. https://doi.org/10.18038/aubtda.346407.

EndNote

Zeybek H, Kaleli C (June 1, 2018) Dynamic k Neighbor Selection for Collaborative Filtering. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 19 2 303–315.

IEEE

[1]H. Zeybek and C. Kaleli, “Dynamic k Neighbor Selection for Collaborative Filtering”, AUJST-A, vol. 19, no. 2, pp. 303–315, June 2018, doi: 10.18038/aubtda.346407.

ISNAD

Zeybek, Halil - Kaleli, Cihan. “Dynamic K Neighbor Selection for Collaborative Filtering”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 19/2 (June 1, 2018): 303-315. https://doi.org/10.18038/aubtda.346407.

JAMA

1.Zeybek H, Kaleli C. Dynamic k Neighbor Selection for Collaborative Filtering. AUJST-A. 2018;19:303–315.

MLA

Zeybek, Halil, and Cihan Kaleli. “Dynamic K Neighbor Selection for Collaborative Filtering”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 19, no. 2, June 2018, pp. 303-15, doi:10.18038/aubtda.346407.

Vancouver

1.Halil Zeybek, Cihan Kaleli. Dynamic k Neighbor Selection for Collaborative Filtering. AUJST-A. 2018 Jun. 1;19(2):303-15. doi:10.18038/aubtda.346407

Dynamic k Neighbor Selection for Collaborative Filtering

Dynamic k Neighbor Selection for Collaborative Filtering

Abstract

Keywords

Abstract

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

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