Journal of computing and information technology, Vol. 22 No. 2, 2014.

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

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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