Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Web Aggregation Approach for Distributed Randomized PageRank
  Algorithms   The PageRank algorithm employed at Google assigns a measure of importance to
each web page for rankings in search results. In our recent papers, we have
proposed a distributed randomized approach for this algorithm, where web pages
are treated as agents computing their own PageRank by communicating with linked
pages. This paper builds upon this approach to reduce the computation and
communication loads for the algorithms. In particular, we develop a method to
systematically aggregate the web pages into groups by exploiting the sparsity
inherent in the web. For each group, an aggregated PageRank value is computed,
which can then be distributed among the group members. We provide a distributed
update scheme for the aggregated PageRank along with an analysis on its
convergence properties. The method is especially motivated by results on
singular perturbation techniques for large-scale Markov chains and multi-agent
consensus.

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The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
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The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
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The categories of this paper are: q-bio
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The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-ph
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The categories of this paper are: dg-ga