A Ranking Algorithm Based on Graph Topology to Generate Reputation or Relevance

We introduce NodeRanking, a new mechanism for ranking the importance of nodes in a graph. Ranking nodes in a graph is not a new problem and some solutions do exist in the literature, such as the well-known algorithms Pagerank, HITS, and SALSA. Our main contribution consists in the fact that the introduced algorithm uses only local information. Thus, the algorithm is truly distributed and it does not need any knowledge of the whole graph. Furthermore, NodeRanking adapts itself to the graph topology, hence, no setting-up process is required. The quality and adaptability of NodeRanking is tested on different graphs (a real social network and a scale-free graph) with different topological properties Finally, we show how the algorithm may be applied either to extract the relevance of Web pages or to infer the reputation of members of a community.