We observe that ranking systems—a theoretical framework for web page ranking and collaborative filtering introduced by Altman and Tennenholtz—and tournament solutions—a well-studied area of social choice theory—are strongly related. This relationship permits a mutual transfer of axioms and solution concepts. As a first step, we formally analyze a tournament solution that is based on Google’s Pa...

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's p...

Web link analysis has been proven to provide significant enhancement to the precision of web search in practice. The PageRank algorithm, used in the Google Search Engine, plays an important role in improving the quality of results by employing an explicit hyperlink structure among the Web pages. The prestige of Web pages defined by PageRank is derived solely from surfers’ random walk on the Web...

The spread of subject gateway sites can have an impact on the other major Web information retrieval tool: the commercial search engine. This is because gateway sites perturb the link structure of the Web, something used to rank matches in search engine results pages. The success of Google means that its PageRank algorithm for ranking the importance of Web pages is an object of particular intere...

To account for strong aging characteristics of citation networks, we modify Google’s PageRank algorithm by initially distributing random surfers exponentially with age, in favor of more recent publications. The output of this algorithm, which we call CiteRank, is interpreted as approximate traffic to individual publications in a simple model of how researchers find new information. We develop a...

A new method for computing the value of citations is introduced and compared with the PageRank algorithm for author ranking. In our proposed approach, the value of each publication is expressed in CENTs (sCientific currENcy Tokens). The publication’s value is then divided by the number of citations made by that publication to yield a value for each citation. As citations are the acknowledgement...

Google’s success derives in large part from its PageRank algorithm, which ranks the importance of webpages according to an eigenvector of a weighted link matrix. Analysis of the PageRank formula provides a wonderful applied topic for a linear algebra course. Instructors may assign this article as a project to more advanced students, or spend one or two lectures presenting the material with assi...

Google’s success derives in large part from its PageRank algorithm, which ranks the importance of webpages according to an eigenvector of a weighted link matrix. Analysis of the PageRank formula provides a wonderful applied topic for a linear algebra course. Instructors may assign this article as a project to more advanced students, or spend one or two lectures presenting the material with assi...