Multiplex communications – Network configuration determination
Reexamination Certificate
2011-08-16
2011-08-16
Ton, Dang T (Department: 2475)
Multiplex communications
Network configuration determination
C707S999002
Reexamination Certificate
active
08000262
ABSTRACT:
A method of computing a measure of similarity between nodes of first and second networks is described. In particular, sets of pairwise scores are computed to find nodes in the individual networks that are good matches to one another. Thus, a pairwise score, referred to as Rij, is computed for a node i in the first network and a node j in the second network. Similar pairwise scores are computed for each of the nodes in each network. The goal of this process is to identify node pairs that exhibit high Rijvalues. According to the technique described herein, the intuition is that nodes i and j are a good match if their neighbors are a good match. This technique produces a measure of “network similarity.” If node feature data also is available, the intuition may be expanded such that nodes i and j are considered a good match if their neighbors are a good match (network similarity) and their node features are a good match (node similarity). Node feature data typically is domain-specific. Using the similarity scores, a common subgraph between the first and second networks then can be computed.
REFERENCES:
patent: 2004/0204925 (2004-10-01), Alon et al.
patent: 2007/0239694 (2007-10-01), Singh et al.
patent: 2008/0276201 (2008-11-01), Risch et al.
Leighton Bonnie Berger
Singh Rohit
Judson David H.
Preval Lionel
Ton Dang T
LandOfFree
Method for identifying network similarity by matching... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method for identifying network similarity by matching..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method for identifying network similarity by matching... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2695803