Download Advances in Artificial Intelligence: 26th Canadian by Mohammad Ali Bagheri, Qigang Gao, Sergio Escalera (auth.), PDF

By Mohammad Ali Bagheri, Qigang Gao, Sergio Escalera (auth.), Osmar R. Zaïane, Sandra Zilles (eds.)

This e-book constitutes the refereed court cases of the twenty fifth Canadian convention on synthetic Intelligence, Canadian AI 2012, held in Regina, SK, Canada, in may possibly 2013. The 17 general papers and 15 brief papers awarded have been rigorously reviewed and chosen from seventy three preliminary submissions and are observed via eight papers from the Graduate scholar Symposium that have been chosen from 14 submissions. The papers disguise various themes inside of AI, corresponding to: details extraction, wisdom illustration, seek, textual content mining, social networks, temporal associations.

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2 Protection of Personal Health Information Uncontrolled access to health information could lead to privacy compromise, breaches of trust, and eventually harm. [23] proposed a role prediction model to protect the electronic medical records (EMR) and privacy of the patients. txt Detecting Health-Related Privacy Leaks in Social Networks Using Text Mining Tools 27 example, [13] study the privacy protection state laws and technology limitations with respect to the electronic medical records. However, protection of personal health information in contents of social networks did not receive as much attention.

G. blogs, forums, and online social networks). PHI relates to the physical or mental health of the individual, including information that consists of the health history of the individual’s family, and information about the health care provider. g. “I have pain in my chest” vs. “I feel your pain”). In this work, we focus on analysis/development of methods protecting privacy of personal health information in online social networks. We believe the online social networks’ growth and the general public involvement makes social networks an excellent candidate for health information privacy research.

Let ψ be any potential constructed by VE. The evidence expanded form of ψ, denoted F (ψ), is the unique expression defining how ψ was built using the multiplication and marginalization operators on the Bayesian network CPTs together with any appropriate evidence potentials. J. Butz, W. L. Madsen For example, consider potential ψ(g, i = 1, j) in (2). F (ψ(g, i = 1, j)), the evidence expanded form, can be easily obtained in a recursive manner as follows: ψ(i = 1, s) · ψ(g, j, s) s ψ(i = 1, s) · ( = s (p(l|g) · p(j|l, s))) l ((p(s|i) · 1(i = 1)) · ( = s (p(l|g) · p(j|l, s)))).

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