Application of vague set in recommender systems

4Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In the paper, vague set theory is introduced into the study of recommender systems to solve its core problem which is similarity. The existence of uncertainty of customer behavior in the course of e-commerce provides a theoretical basis for the introduction of Vague set. Recommendation ofgoods relies on the degree of similarity between customers or goods, while the calculation of similarity is a mature area in the research of Vague set. First, Different customer types are identified according to the general shopping way in e-commerce. Then based on the customer classification, statistical methods are used to define the Vague value of the commodity. This method makes a perfect combination e-commerce recommendation system and Vague set and provides new idea for the study of e-commerce recommendation system. © Springer-Verlag Berlin Heidelberg 2013.

Cite

CITATION STYLE

APA

Cui, C., Zang, Z., Liu, F., & Qu, Y. (2013). Application of vague set in recommender systems. In LISS 2012 - Proceedings of 2nd International Conference on Logistics, Informatics and Service Science (pp. 1353–1359). https://doi.org/10.1007/978-3-642-32054-5_192

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free