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Link prediction plays an important role in complex network analysis. It is to predict the existence of an unknown link or a future link in a network. Classical methods for link prediction evaluate the similarity of vertices based on common neighbors, and denote that every common neighbor makes equal contribution to the connection likelihood. However, common neighbors may play different roles depending...
In order to make the smart home system to have the ability of learning user behavior actively and provide services spontaneously, this paper introduced user behavior prediction model which combined back propagation neural network (BPNN) with Hadoop parallel computing to the traditional smart home system, numerous user-generated behavior and environmental parameters data are packaged in particular...
Link prediction in network attempts to predict the exist-yet-unknown links or future links in accordance with the node properties and the network typology. It has been used in many domains such as social network, biology experiment, and criminal investigations. Classical methods are based on graph topology structure and path features but few consider clustering information. Actually, clustering information...
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