Worst-case Analysis of Set Union Algorithms
Journal of the ACM (JACM)
Data structures and network algorithms
Data structures and network algorithms
Efficiency of a Good But Not Linear Set Union Algorithm
Journal of the ACM (JACM)
Combinatorics, Probability and Computing
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Cache Cookies for Browser Authentication (Extended Abstract)
SP '06 Proceedings of the 2006 IEEE Symposium on Security and Privacy
De-anonymizing Social Networks
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
Journal of the ACM (JACM)
Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Evolution of a location-based online social network: analysis and models
Proceedings of the 2012 ACM conference on Internet measurement conference
What's in a name?: an unsupervised approach to link users across communities
Proceedings of the sixth ACM international conference on Web search and data mining
Exploiting innocuous activity for correlating users across sites
Proceedings of the 22nd international conference on World Wide Web
Privacy and online social networks: can colorless green ideas sleep furiously?
IEEE Security and Privacy
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An incisive understanding of human lifestyles is not only essential to many scientific disciplines, but also has a profound business impact for targeted marketing. In this paper, we present LifeSpec, a computational framework for exploring and hierarchically categorizing urban lifestyles. Specifically, we have developed an algorithm to connect multiple social network accounts of millions of individuals and collect their publicly available heterogeneous behavioral data as well as social links. In addition, a nonparametric Bayesian approach is developed to model the lifestyle spectrum of a group of individuals. To demonstrate the effectiveness of LifeSpec, we conducted extensive experiments and case studies, with a large dataset we collected covering 1 million individuals from 493 cities. Our results suggest that LifeSpec offers a powerful paradigm for 1) revealing an individual's lifestyle from multiple dimensions, and 2) uncovering lifestyle commonalities and variations of a group with various demographic attributes, such as vocation, education, gender, sexual orientation, and place of residence. The proposed method provides emerging implications for personalized recommendation and targeted advertising.