Encyclopedia of Systems and Control

Living Edition
| Editors: John Baillieul, Tariq Samad

Markov Chains and Ranking Problems in Web Search

  • Hideaki IshiiEmail author
  • Roberto Tempo
Living reference work entry

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DOI: https://doi.org/10.1007/978-1-4471-5102-9_135-2

Abstract

Markov chains refer to stochastic processes whose states change according to transition probabilities determined only by the states of the previous time step. They have been crucial for modeling large-scale systems with random behavior in various fields such as control, communications, biology, optimization, and economics. In this entry, we focus on their recent application to the area of search engines, namely, the PageRank algorithm employed at Google, which provides a measure of importance for each page in the web. We present several researches carried out with control theoretic tools such as aggregation, distributed randomized algorithms, and PageRank optimization. Due to the large size of the web, computational issues are the underlying motivation of these studies.

Keywords

Aggregation Distributed randomized algorithms Markov chains Optimization PageRank Search engines World Wide Web 
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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceTokyo Institute of TechnologyYokohamaJapan
  2. 2.CNR-IEIIT, Politecnico di TorinoTorinoItaly

Section editors and affiliations

  • Fabrizio Dabbene
    • 1
  1. 1.Systems Modeling & Control GroupCNR-IEIITTorinoItaly