The paper presents a new algorithm FPPR which updates PageRanks of directed network after topological changes in the graphs. is capable regenerating scores on node and link addition/deletion. expected value random surfers are used for updating newly added nodes as well impacted chain where nodes/links or removed. complexity k addition $$\mathcal {O}(k\times d^{(k)}_{avg})$$ $$d^{(k)}_{avg}$$ av...

Originally created for Web ranking, PageRank has become a major method for evaluating popularity of nodes in information networks. Besides its primary application in search engines, PageRank is successfully used for solving other important problems such as graph partitioning [3], spam detection [8], and finding gems in scientific citations [6], just to name a few. The PageRank [5] is defined as...

The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by taking into account the link structure of the Web. PageRank assigns to a page a score proportional to the number of times a random surfer would visit that page, if it surfed indefinitely from page to page, following all outlinks from a page with equal probability. We propose to improve PageRa...

We propose an adaptive reorderedmethod to deal with the PageRank problem. It has been shown that one can reorder the hyperlink matrix of PageRank problem to calculate a reduced system and get the full PageRank vector through forward substitutions. This method can provide a speedup for calculating the PageRank vector.We observe that in the existing reorderedmethod, the cost of the recursively re...

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to add...