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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...
Thanks to the ubiquitous computing, the scale of data collection in various fields has been growing rapidly. Medicine is one of the fields that can benefit from the big data. However, it is faced with a big challenge because medical datasets are normally in high dimensions. Therefore, reducing dimensionality and finding the optimal set of features or attributes is of great importance. This paper presents...
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...
Traffic matrices (TMs) are very important for traffic engineering and if they can be predicted, the network operations can be made beforehand. However, existing prediction methods are neither accurate nor efficient in practice. In this paper, we utilize the spatio-temporal property and low rank nature to directly predict the total TMs. The problem is that conventional matrix interpolation only works...
According to the characteristics of massive input and output data, complicated production process and the difficulty to acquire accurate mathematical model of the non-linear blast furnace system, this paper proposes a fuzzy system modeling method based on data driving. This paper utilizes the fuzzy clustering algorithms combined nearest neighbor clustering and fuzzy c-means clustering to classify...
As is known to us, the handover latency of FMIPv6 in its predictive mode is given little concerns. However our previous work [4] shows that FMIPv6 may suffer long handover latency in its predictive mode, and [4] identifies three key issues raising such problems. In this paper, we propose a practical cross-layer fast handover management mechanism (PCLF) to address these issues and improve success rate...
Transporting hybrid coded video over wireless channel is very challenging. Efficient coding and compression techniques are required to meet the QoS (Quality of Service) requirements of such services. H.264, the latest coding and compression standard from ITU-T, is currently dominating the field by offering a flexible architecture and compression gain of up to 50%. In H.264, intra frame prediction...
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