PageRank: This is an algorithm which ranks a web-page among set of web-page on WWW by considering a large set of different variables.
LinkRank: is a method of quantifying the modularity of social links in directed network. The original paper assumes modularities in un-directed networks and optimizes it for directed networks.
WikiFactor: "A new metric is introduced, inspired by the Hirsch {\it h-index}, to measure the impact of a wiki site. A table of wikiFactors is presented for a number of wikis, in particular those oriented towards scientific topics. The wikiFactor is defined as the number of web pages, wF, that have had $\ge 1000$wF visits."
Referring to these links one reasonable question would be haw to rank communities, services, privacy settings in sub-graphs or along the whole graph. But what one could buy out of this? Well, considering services provisions and service management, one should provide provide load balancing, some what deterministically routing, or have surgically prune out bad guys (cheaters in MMOG, attackers, or selfish guys).
@ LinkRank: One can predict link, LinkPrdict, by predicting previously un-observed relationship and hence behavior. There are many exciting applications of this particular area of network science. Most research in the area of link prediction has been restricted to scoring based on a single measure within network topologies. While the research considers new measure and placing existing measures in the context of a machine learning task. "We are also casting the problem as a high class imbalance task."
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