Google, the largest search engine worldwide, adopts PageRank technology to determine the rank of website listings. This paper describes how damping factor is a critical factor in changing a website’s ranking in traditional Google PageRank technology. A modified algorithm based on input–output ratio concept is proposed to substitute for the damping factor. Besides there is no need to choose an o...

Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the stochastic Google matrix G. The algorithm lumps all dangling nodes into a single node. We express lumping as a similarity transformation of G, and show that the PageRank of the nondangling nodes can be computed separately from that of the dangling nodes. The algorithm applies the power method onl...

PageRank, the popular link-analysis algorithm for ranking web pages, assigns a query and user independent estimate of “importance” to web pages. Query and user sensitive extensions of PageRank, which use a basis set of biased PageRank vectors, have been proposed in order to personalize the ranking function in a tractable way. We analytically compare three recent approaches to personalizing Page...

PageRank has been widely used to measure the importance of web pages based on their interconnections in the web graph. Mathematically speaking, PageRank can be explained using a Markov random walk model, in which only the direct outlinks of a page contribute to its transition probability. In this paper, we propose improving the PageRank algorithm by looking N-step ahead when constructing the tr...

In this study, the Finite-Element Model Updating (FEMU) technique is used to identify hyperelastic parameters from only one heterogeneous test. A residual considering measured and identified stretches as well global reaction force of specimen built. The originality paper investigate feasibility resolution minimisation problem using Inverse-PageRank-particle swarm optimisation (PSO) for identify...

J. Hopcroft and D. Sheldon originally introduced the PageRank game to investigate the self-interested behavior of web authors who want to boost their PageRank by using game theoretical approaches. The PageRank game is a multiplayer game where players are the nodes in a directed web graph and they place their outlinks to maximize their PageRank value. They give best response strategies for each ...

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web page...