Title :
Content-Based Recommendation System Based on Vague Sets
Author :
Fujiang Sun ; Yu Shi ; Weiping Wang
Author_Institution :
Coll. of Sci., China Agric. Univ., Beijing, China
Abstract :
Focused on the trouble of the features representation of merchandise in content-Based recommendation system, in this paper, the theory of vague sets, Gaussian function and characteristics of uncertainty were used to represent features with vague value. On this basis, the general steps of content-Based recommendation with Vague Sets were given in the paper, in order to get a new idea and method to recommender systems designers. Finally, some recommender formula with different features are given, which will be conducive to the work of the actual recommendation. Select different formula according different condition will improve the quality and accuracy of the recommendation.
Keywords :
recommender systems; set theory; content-based recommendation system; recommendation accuracy; recommendation quality; recommender formula; recommender systems designer; vague sets; Adaptive filters; Animation; Educational institutions; Motion pictures; Recommender systems; Uncertainty; Content-Based Recommendation; Recommender Systems; Similarity; Vague Sets;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
DOI :
10.1109/IHMSC.2013.218