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

Novel version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network using Social Impact