The PageRank is a widely used scoring function of networks in general and of the World Wide Web graph in particular. The PageRank is defined for directed graphs, but in some special cases applications for undirected graphs occur. In the literature it is widely noted that the PageRank for undirected graphs are proportional to the degrees of the vertices of the graph. We prove that statement for ...

The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts – including ranking websites – and can be interpreted as the average portion of time spent at the node by an infinite random walk. We consider the problem of maximizing the PageRank of a node by selecting some of the edges from a set of edges that are ...

Personalized PageRank expresses backlink-based page quality around user-selected pages in a similar way as PageRank expresses quality over the entire Web. Existing personalized PageRank algorithms can however serve on-line queries only for a restricted choice of page selection. In this paper we achieve full personalization by a novel algorithm that computes a compact database of simulated rando...

The paper attempts to provide an alternative method for measuring the importance of scientific papers based on the Google’s PageRank. The method is a meaningful extension of the common integer counting of citations and is then experimented for bringing PageRank to the citation analysis in a large citation network. It offers a more integrated picture of the publications’ influence in a specific ...

Different models have been proposed for improving the results of Web search by taking into account the link structure of the Web. The PageRank algorithm models the behavior of a random surfer alternating between random jumps to new pages and following out links with equal probability. We propose to improve on PageRank by using an intelligent surfer that combines link structure and content to de...

This paper presents our studies on the rearrangement of links in the structure of websites for the purpose of improving the valuation of a page or group of pages as established by a ranking function as Google’s PageRank. We build our topological taxonomy starting from unidirectional and bidirectional rooted trees, and up to more complex hierarchical structures as cyclical rooted trees (obtained...

We study a problem of quick detection of top-k Personalized PageRank lists. This problem has a number of important applications such as finding local cuts in large graphs, estimation of similarity distance and name disambiguation. In particular, we apply our results to construct efficient algorithms for the person name disambiguation problem. We argue that when finding top-k Personalized PageRa...

The PageRank algorithm demonstrates the significance of the computation of document ranking of general importance or authority in Web information retrieval. However, doing a PageRank computation for the whole Web graph is both time-consuming and costly. State of the art Web crawler based search engines also suffer from the latency in retrieving a complete Web graph for the computation of PageRa...

Much has been written in recent years about the blogosphere and its impact on political, educational and scientific debates. Lately the issue has received significant attention from the industry. As the blogosphere continues to grow, even doubling its size every six months, this paper investigates its apparent impact on the overall Web itself. We use the popular Google PageRank algorithm which ...

In this article we will look at the PageRank algorithm used as part of the ranking process of different Internet pages in search engines by for example Google. This article has its main focus in the understanding of the behavior of PageRank as the system dynamically changes either by contracting or expanding such as when adding or subtracting nodes or links or groups of nodes or links. In parti...