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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2016
عنوان انگلیسی مقاله:
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks
ترجمه فارسی عنوان مقاله:
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks
منبع:
IEEE - IEEE ICC 2016 SAC Cloud Communications and Networking
نویسنده:
Chencheng Li1, Pan Zhou2†,Yingxue Zhou3, Kaigui Bian4,Tao Jiang5,Susanto Rahardja6
چکیده انگلیسی:
With the rapid growth of Internet technologies,
cloud computing and social networks have become ubiquitous.
An increasing number of people participate in social networks
and massive online social data are obtained. In order to exploit
knowledge from copious amounts of data obtained and predict
social behavior of users, we urge to realize data mining in
social networks. Almost all online websites use cloud services
to effectively process the large scale of social data, which are
gathered from distributed data centers. These data are so largescale, high-dimension and widely distributed that we propose a
distributed sparse online algorithm to handle them. Additionally,
privacy-protection is an important point in social networks. We
should not compromise the privacy of individuals in networks,
while these social data are being learned for data mining. Thus we
also consider the privacy problem in this article. Our simulations
shows that the appropriate sparsity of data would enhance the
performance of our algorithm and the privacy-preserving method
does not significantly hurt the performance of the proposed
algorithm.
Index Terms: Cloud computing | social networks | sparse | dis tributed online learning
قیمت: رایگان
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