2013 LearningGeographicalPreferences

• (Liu et al., 2013) ⇒ Bin Liu, Yanjie Fu, Zijun Yao, and Hui Xiong. (2013). “Learning Geographical Preferences for Point-of-interest Recommendation.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487673

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Cited By

• http://scholar.google.com/scholar?q=%222013%22+Learning+Geographical+Preferences+for+Point-of-interest+Recommendation
• http://dl.acm.org/citation.cfm?id=2487575.2487673&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; human mobility; location-based social networks; point-of-interest; recommender systems; user profiling

Abstract

The problem of point of interest (POI) recommendation is to provide personalized recommendations of places of interests, such as restaurants, for mobile users. Due to its complexity and its connection to location based social networks (LBSNs), the decision process of a user choose a POI is complex and can be influenced by various factors, such as user preferences, geographical influences, and user mobility behaviors. While there are some studies on POI recommendations, it lacks of integrated analysis of the joint effect of multiple factors. To this end, in this paper, we propose a novel geographical probabilistic factor analysis framework which strategically takes various factors into consideration. Specifically, this framework allows to capture the geographical influences on a user's check-in behavior. Also, the user mobility behaviors can be effectively exploited in the recommendation model. Moreover, the recommendation model can effectively make use of user check-in count data as implicity user feedback for modeling user preferences. Finally, experimental results on real-world LBSNs data show that the proposed recommendation method outperforms state-of-the-art latent factor models with a significant margin.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 LearningGeographicalPreferences	Hui Xiong Bin Liu Yanjie Fu Zijun Yao			Learning Geographical Preferences for Point-of-interest Recommendation				10.1145/2487575.2487673		2013