Fuzzy Markov Chains and Experiments with FuzzRank, an Alternative to PageRank

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Authors

Case, Ryan

Date

2016-04-28

Type

thesis

Language

eng

Keyword

Fuzzy Set Theory , PageRank , FuzzRank , Fuzzy Markov Chain

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Abstract

The theory of Markov chains has been applied successfully in several situations, for example in the PageRank algorithm which powers Google search. In this thesis we study the foundations of fuzzy logic and Markov chains before introducing fuzzy Markov chains. Fuzzy Markov chains were introduced in 1970 as an alternative to the usual Markov chains and have some interesting properties that may make them more desirable for some applications. We will consider some of these properties and see how they differ from the usual Markov chains. We will also study an application of fuzzy Markov chains called FuzzRank, a twist on the aforementioned PageRank algorithm used for web search. Finally, we will consider a further generalization of the fuzzy Markov chains where we allow some flexibility in the operations we use during matrix multiplication to compute our results.

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Thesis (Master, Computing) -- Queen's University, 2016-04-28 18:23:20.96

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Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
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Creative Commons - Attribution - CC BY
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.

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