DocumentCode
620239
Title
Based on the similarity of interval-valued intuitionistic fuzzy sets defined by entropy in the application of commodity recommendation
Author
Luo Peng ; Li Yongli ; Wu Chong
Author_Institution
Sch. of Econ. & Manage., Harbin Inst. of Technol., Harbin, China
fYear
2013
fDate
25-27 May 2013
Firstpage
3046
Lastpage
3050
Abstract
The effective and accurate recommendation method is called for the fast development of E-commence. In the existed recommendation algorithms, there are two biggest problems: data sparseness and manipulation problem. In our paper, we propose a new view to recommend which based on similarity of two interval-valued intuitionistic fuzzy sets defined by entropy. And we have proved that the recommendation algorithm is feasible.
Keywords
electronic commerce; entropy; fuzzy logic; fuzzy set theory; recommender systems; E-commence; commodity recommendation algorithm; data manipulation problem; data sparseness; entropy; interval valued intuitionistic fuzzy set; recommendation; Bismuth; Collaboration; Computers; Entropy; Fuzzy sets; Recommender systems; Vectors; Interval-valued intuitionistic fuzzy set Entropy; Recommending Algorithm; Similarity measure;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location
Guiyang
Print_ISBN
978-1-4673-5533-9
Type
conf
DOI
10.1109/CCDC.2013.6561468
Filename
6561468
Link To Document