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[**Detecting Memory and Structure in Human Navigation Patterns Using Markov Chain Models of Varying Order** ]{}\
Philipp Singer$^{1,\ast}$, Denis Helic$^{2}$, Behnam Taraghi$^{3}$, Markus Strohmaier$^{1,4}$\
**[1]{} GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany\
**[2]{} Technical University of Graz, Knowledge Technologies Institute, Graz, Austria\
**[3]{} Technical University of Graz, Institute for Information Systems and Computer Media, Graz, Austria\
**[4]{} University Koblenz-Landau, Institute for Web Science and Technologies, Koblenz, Germany\
$\ast$ E-mail: philipp.singer@gesis.org********

Abstract {#abstract .unnumbered}
========

One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page