tag recommendation based on bayesian principle

ISCAS OpenIR > 2010软件所会议论文

	tag recommendation based on bayesian principle
	Wang Zhonghui; Deng Zhihong
	2010
会议名称	6th International Conference on Advanced Data Mining and Applications, ADMA 2010
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码	191-201
会议日期	40848
会议地点	Chongqing, China
收录类别	ei
出版地	Germany
ISSN	3029743
ISBN	3642173128
部门归属	(1) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, China
摘要	Social tagging systems have become increasingly a popular way to organize online heterogeneous resources. Tag recommendation is a key feature of social tagging systems. Many works has been done to solve this hard tag recommendation problem and has got same good results these years. Taking into account the complexity of the tagging actions, there still exist many limitations. In this paper, we propose a probabilistic model to solve this tag recommendation problem. The model is based on Bayesian principle, and its very robust and efficient. For evaluating our proposed method, we have conducted experiments on a real dataset extracted from BibSonomy, an online social bookmark and publication sharing system. Our performance study shows that our method achieves good performance when compared with classical approaches. © 2010 Springer-Verlag.
关键词	Algorithms Bayesian Networks Data Mining Thesauri
主办者	National Natural Science Foundation of China; Chongqing Science and Technology Commission; Chongqing Academy of Science and Technology
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/8926
专题	2010软件所会议论文
推荐引用方式 GB/T 7714	Wang Zhonghui,Deng Zhihong. tag recommendation based on bayesian principle[C]. Germany,2010:191-201.

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