Gualdi, Stanislao Medo, Matúš Zhang, Yi-Cheng 2011-08-12 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. application/pdf https://folia.unifr.ch/global/documents/302186 https://folia.unifr.ch/documents/302186/files/zha_ios.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1209/0295-5075/96/18004 info:eu-repo/semantics/openAccess License undefined Europhysics Letters. - 2011, vol. 96, no. 1, p. 18004 info:eu-repo/classification/udc/53 Influence, originality and similarity in directed acyclic graphs http://purl.org/coar/resource_type/c_6501