2010 TheTopicPerspectiveModelforSoci

• (Lu et al., 2010) ⇒ Caimei Lu, Xiaohua Hu, Xin Chen, Jung-Ran Park, TingTing He, and Zhoujun Li. (2010). “The Topic-perspective Model for Social Tagging Systems.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835891

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Cited By

• http://scholar.google.com/scholar?q=%22The+topic-perspective+model+for+social+tagging+systems%22+2010
• http://portal.acm.org/citation.cfm?id=1835891&preflayout=flat#citedby

Quotes

Abstract

In this paper, we propose a new probabilistic generative model, called Topic-Perspective Model, for simulating the generation process of social annotations. Different from other generative models, in our model, the tag generation process is separated from the content term generation process. While content terms are only generated from resource topics, social tags are generated by resource topics and user perspectives together. The proposed probabilistic model can produce more useful information than any other models proposed before. The parameters learned from this model include: (1) the topical distribution of each document, (2) the perspective distribution of each user, (3) the word distribution of each topic, (4) the tag distribution of each topic, (5) the tag distribution of each user perspective, (6) and the probabilistic of each tag being generated from resource topics or user perspectives. Experimental results show that the proposed model has better generalization performance or tag prediction ability than other two models proposed in previous research.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 TheTopicPerspectiveModelforSoci	Xiaohua Hu Caimei Lu Xin Chen Jung-Ran Park TingTing He Zhoujun Li			The Topic-perspective Model for Social Tagging Systems		KDD-2010 Proceedings		10.1145/1835804.1835891		2010