2013 UnsupervisedLinkPredictionUsing

• (Kuo et al., 2013) ⇒ Tsung-Ting Kuo, Rui Yan, Yu-Yang Huang, Perng-Hwa Kung, and Shou-De Lin. (2013). “Unsupervised Link Prediction Using Aggregative Statistics on Heterogeneous Social Networks.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487614

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Unsupervised+Link+Prediction+Using+Aggregative+Statistics+on+Heterogeneous+Social+Networks
• http://dl.acm.org/citation.cfm?id=2487575.2487614&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; heterogeneous social network; link prediction; linked representations; probabilistic graphical model; social network mining; sociology

Abstract

The concern of privacy has become an important issue for online social networks. In services such as Foursquare.com, whether a person likes an article is considered private and therefore not disclosed; only the aggregative statistics of articles (i.e., how many people like this article) is revealed. This paper tries to answer a question: can we predict the opinion holder in a heterogeneous social network without any labeled data? This question can be generalized to a link prediction with aggregative statistics problem. This paper devises a novel unsupervised framework to solve this problem, including two main components: (1) a three-layer factor graph model and three types of potential functions; (2) a ranked-margin learning and inference algorithm. Finally, we evaluate our method on four diverse prediction scenarios using four datasets: preference (Foursquare), repost (Twitter), response (Plurk), and citation (DBLP). We further exploit nine unsupervised models to solve this problem as baselines. Our approach not only wins out in all scenarios, but on the average achieves 9.90% AUC and 12.59% NDCG improvement over the best competitors. The resources are available at http://www.csie.ntu.edu.tw/~d97944007 / aggregative /

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 UnsupervisedLinkPredictionUsing	Shou-De Lin Tsung-Ting Kuo Rui Yan Yu-Yang Huang Perng-Hwa Kung			Unsupervised Link Prediction Using Aggregative Statistics on Heterogeneous Social Networks				10.1145/2487575.2487614		2013