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arXiv · 1108.3691

Influence, originality and similarity in directed acyclic graphs

Stanislao Gualdi·Matus Medo·Yi-Cheng Zhang
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Abstract

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.

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Stanislao Gualdi, Matus Medo, Yi-Cheng Zhang. 2011-08-18. Influence, originality and similarity in directed acyclic graphs. https://doi.org/10.1209/0295-5075%2F96%2F18004

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