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ISSN: 1536-1268
Nicholas Lane , Dartmouth College, hanover
Ye Xu , Dartmouth College, Hanover
Hong Lu , Dartmouth College, Hanover
Shane Eisenman , Columbia Univ, New York
Tanzeem Choudhury , Dartmouth College, Hanover
Andrew Campbell , Dartmouth College, Hanover
Human behavior modeling at a large-scale and under real-world conditions is still an open problem. Existing classification models do not always perform well on a diverse population. Training personalized models that incorporate different contextual conditions and individual user characteristics are effective in addressing this challenge. However, this approach burdens the users with collecting and manually labeling their own training data which is not scalable. In this article, we propose CoCo (Cooperative Communities), a learning framework that leverages different types of everyday social connections between people to personalize classification models. CoCo exploits social networks to selectively combine small contributions of labeled data from people with shared context or user characteristics. Under CoCo a personalized classifier is trained for each individual user, but by exploiting social networks, the burden of providing training data can be spread over the entire community.
A.0 General, B Hardware, I.2 Artificial Intelligence, I.1.4 Applications, I.5 Pattern Recognition, I.2 Artificial Intelligence, G.3.h Probabilistic algorithms, G.3.e Markov processes, C.5.7 Wearable Computers, C.3.h Ubiquitous computing, C.2.2.a Applications, C.2.4 Distributed Systems, C.2.8 Mobile Computing, C.3.h Ubiquitous computing, C.3.h Ubiquitous computing, H.1.2.b Human-centered computing, H.5.2 User Interfaces, J.9.a Location-dependent and sensitive, J.9.d Pervasive computing, J.9 Mobile Applications, J.9.f Wireless sensor networks, J.9.e Wearable computers and body area networks, I.5.2.a Classifier design and evaluation, I.1.4 Applications, I.5.4.j Remote sensing

H. Lu, Y. Xu, N. Lane, S. Eisenman, A. Campbell and T. Choudhury, "Cooperative Communities (CoCo): Exploiting Social Networks for Large-scale Modeling of Human Behavior," in IEEE Pervasive Computing.
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