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pro vyhledávání: '"Lauren M. Nelsen"'
Autor:
Lauren M. Nelsen, Paul Horn
Publikováno v:
Network Science. 9:S4-S22
Personalized PageRank has found many uses in not only the ranking of webpages, but also algorithmic design, due to its ability to capture certain geometric properties of networks. In this paper, we study the diffusion of PageRank: how varying the jum
Autor:
Lauren M. Nelsen, Paul Horn
Publikováno v:
Complex Networks and Their Applications VIII ISBN: 9783030366865
COMPLEX NETWORKS (1)
COMPLEX NETWORKS (1)
Personalized PageRank has found many uses in not only the ranking of webpages, but also algorithmic design, due to its ability to capture certain geometric properties of networks. In this paper, we study the diffusion of PageRank: how varying the jum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a719528e354228e1616750331ec192b
https://doi.org/10.1007/978-3-030-36687-2_2
https://doi.org/10.1007/978-3-030-36687-2_2
Autor:
Jennifer Diemunsch, Nathan Graber, Derrick Stolee, Charlie Suer, Victor Larsen, Lauren M. Nelsen, Lucas Kramer, Luke L. Nelsen, Devon Sigler
Let $c:E(G)\to [k]$ be an edge-coloring of a graph $G$, not necessarily proper. For each vertex $v$, let $\bar{c}(v)=(a_1,\ldots,a_k)$, where $a_i$ is the number of edges incident to $v$ with color $i$. Reorder $\bar{c}(v)$ for every $v$ in $G$ in no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f39d2850420f2bef8c85451c6501e58b
http://arxiv.org/abs/1506.08345
http://arxiv.org/abs/1506.08345