DocumentCode :
578071
Title :
Mining latent tag group based on tag dependency relation for recommendation in collaborative tagging systems
Author :
Liu, Yu ; Cai, Yi ; Zhang, Guang-Yi ; Zhao, Hong-Ke ; Chen, Jun-Ting ; Min, Hua-Qing
Author_Institution :
Sch. of Software Eng., South China Univ. of Technol., Guangzhou, China
Volume :
1
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
102
Lastpage :
106
Abstract :
Currently, collaborative tagging systems have been applied in recommendation systems [2] on a large scale, during which the analysis of tags group is unavoidable. However, a sparsity problem is interfering with most of the current collaborative tagging systems, and there are only a few folks using a considerable number of tags to describe one resource. Through the deep investigation to the statistical relation between the tags in collaborative tagging systems, a mining method named BTDR based on the latent dependence between tags is proposed in this paper. We also conduct experiments to evaluate the proposed method.
Keywords :
data mining; recommender systems; statistical analysis; BTDR mining method; collaborative tagging systems; latent dependence; latent tag group mining; recommendation systems; sparsity problem; statistical relation; tag dependency relation; Abstracts; Collaborative tagging systems; Tags dependence; Tags group;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6358894
Filename :
6358894
Link To Document :
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