Influence, originality and similarity in directed acyclic graphs
- Gualdi, Stanislao Physics Department, University of Fribourg, Switzerland
- Medo, Matúš Physics Department, University of Fribourg, Switzerland
- Zhang, Yi-Cheng Physics Department, University of Fribourg, Switzerland - Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology, Chengdu, China
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12.08.2011
Published in:
- Europhysics Letters. - 2011, vol. 96, no. 1, p. 18004
English
We introduce a framework for network analysis based on random walks on directed acyclic graphs where the probability of passing through a given node is the key ingredient. We illustrate its use in evaluating the mutual influence of nodes and discovering seminal papers in a citation network. We further introduce a new similarity metric and test it in a simple personalized recommendation process. This metric's performance is comparable to that of classical similarity metrics, thus further supporting the validity of our framework.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
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- English
- Classification
- Physics
- License
- License undefined
- Identifiers
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- RERO DOC 28319
- DOI 10.1209/0295-5075/96/18004
- Persistent URL
- https://folia.unifr.ch/unifr/documents/302186
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