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Izvorni znanstveni članak
https://doi.org/10.2498/cit.1002223
Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique
Mohammad-Hossein Nadimi-Shahraki
; Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran
Mozhde Bahadorpour
; Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran
| Puni tekst: engleski, pdf (283 KB) | str. 105-113 | citiraj | |
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APA 6th Edition Nadimi-Shahraki, M. i Bahadorpour, M. (2014). Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique. Journal of computing and information technology, 22 (2), 105-113. https://doi.org/10.2498/cit.1002223 MLA 8th Edition Nadimi-Shahraki, Mohammad-Hossein i Mozhde Bahadorpour. "Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique." Journal of computing and information technology, vol. 22, br. 2, 2014, str. 105-113. https://doi.org/10.2498/cit.1002223. Citirano 20.02.2020. Chicago 17th Edition Nadimi-Shahraki, Mohammad-Hossein i Mozhde Bahadorpour. "Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique." Journal of computing and information technology 22, br. 2 (2014): 105-113. https://doi.org/10.2498/cit.1002223 Harvard Nadimi-Shahraki, M., i Bahadorpour, M. (2014). 'Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique', Journal of computing and information technology, 22(2), str. 105-113. https://doi.org/10.2498/cit.1002223 Vancouver Nadimi-Shahraki M, Bahadorpour M. Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique. Journal of computing and information technology [Internet]. 2014 [pristupljeno 20.02.2020.];22(2):105-113. https://doi.org/10.2498/cit.1002223 IEEE M. Nadimi-Shahraki i M. Bahadorpour, "Cold-start Problem in Collaborative Recommender Systems: Efficient Methods Based on Ask-to-rate Technique", Journal of computing and information technology, vol.22, br. 2, str. 105-113, 2014. [Online]. https://doi.org/10.2498/cit.1002223 |
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Sažetak
To develop a recommender system, the collaborative filtering is the best known approach, which considers the ratings of users who have similar rating profiles or rating patterns. Consistently, it is able to compute the similarity of users when there are enough ratings expressed by users. Therefore, a major challenge of the collaborative filtering approach can be how to make recommendations for a new user, that is called cold-start user problem. To solve this problem, there have been proposed a few efficient methods based on ask-to-rate technique in which the profile of a new user is made by integrating information gained from a quick interview. This paper is a review of these proposed methods and how to use the ask-to-rate technique. Consequently, they are categorized into non-adaptive and adaptive methods. Then, each category is analyzed and their methods are compared.
Ključne riječi
recommender systems; collaborative filtering; new user; user cold-start
Hrčak ID: 125742
URI
https://hrcak.srce.hr/125742
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