Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Evolutionary network analysis has found an increasing interest in the literature because of the importance of different kinds of dynamic social networks, email networks, biological networks, and social streams. When a network evolves, the results of data mining algorithms such as community detection need to be correspondingly updated. Furthermore, the specific kinds of changes to the structure of the network, such as the impact on community structure or the impact on network structural parameters, such as node degrees, also needs to be analyzed. Some dynamic networks have a much faster rate of edge arrival and are referred to as network streams or graph streams. The analysis of such networks is especially challenging, because it needs to be performed with an online approach, under the one-pass constraint of data streams. The incorporation of content can add further complexity to the evolution analysis process. This survey provides an overview of the vast literature on graph evolution analysis and the numerous applications that arise in different contexts. © 2014 ACM.
Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
M.J. Slattery, Joan L. Mitchell
IBM J. Res. Dev
Yigal Hoffner, Simon Field, et al.
EDOC 2004
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering