Generalization of the PageRank Model
This work provides an incremental improvement to web ranking algorithms, potentially benefiting search engine optimization and network analysis.
The paper tackles the problem of generalizing the PageRank model for webgraph centralities by extending it to valued directed graphs and heterogeneous dampening coefficients, resulting in a more flexible model that can be applied using visitation counts.
This paper develops a generalization of the PageRank model of page centralities in the global webgraph of hyperlinks. The webgraph of adjacencies is generalized to a valued directed graph, and the scalar dampening coefficient for walks through the graph is relaxed to allow for heterogeneous values. A visitation count approach may be employed to apply the more general model, based on the number of visits to a page and the page's proportionate allocations of these visits to other nodes of the webgraph.