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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2015-02-24 14:38:30 -0500 |
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| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2015-02-24 14:38:30 -0500 |
| commit | 132e429a3a642bed57975056a8496ebdd6511976 (patch) | |
| tree | a87db50331a85bcc867d28f9bccf9761f5829859 /paper | |
| parent | d1003f5a735aa7b20a3491efe0424adb5ae4e4e1 (diff) | |
| download | cascades-132e429a3a642bed57975056a8496ebdd6511976.tar.gz | |
Fix typo in intro
Diffstat (limited to 'paper')
| -rw-r--r-- | paper/sections/intro.tex | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/paper/sections/intro.tex b/paper/sections/intro.tex index 39f5089..d263860 100644 --- a/paper/sections/intro.tex +++ b/paper/sections/intro.tex @@ -15,7 +15,7 @@ connectivity, routing, gossip algorithms, etc. %learn a graph from the diffusion process? A diffusion process taking place over a graph provides valuable information about the presence and weights of its edges. \emph{Influence cascades} are a -specific type of diffusion processes in which a particular infection behavior +specific type of diffusion processes in which a particular infectious behavior spreads over the nodes of the graph. By only observing the ``infection times'' of the nodes in the graph, one might hope to recover the underlying graph and the parameters of the cascade model. This problem is known in the literature as |