  Nowadays, information describing navigation behaviour of internet users are
used in several fields, e-commerce, economy, sociology and data science. Such
information can be extracted from different knowledge bases, including
business-oriented ones. In this paper, we propose a new model for the PageRank,
CheiRank and 2DRank algorithm based on the use of clickstream and pageviews
data in the google matrix construction. We used data from Wikipedia and
analysed links between over 20 million articles from 11 language editions. We
extracted over 1.4 billion source-destination pairs of articles from SQL dumps
and more than 700 million pairs from XML dumps. Additionally, we unified the
pairs based on the analysis of redirect pages and removed all duplicates.
Moreover, we also created a bigger network of Wikipedia articles based on all
considered language versions and obtained multilingual measures. Based on real
data, we discussed the difference between standard PageRank, Cheirank, 2DRank
and measures obtained based on our approach in separate languages and
multilingual network of Wikipedia.
