Analýza struktury českého webu pomocí grafových metod

This thesis is useful for individual researchers seeking to obtain data about specific parts of the Internet, as well as for marketers looking to identify high-authority websites for advertising. It focuses on analyzing the structure of the Czech web domain space using graph-based methods. A distributed web crawler has been developed to collect hyperlinks and metadata from .cz domains, and the resulting data have been stored and processed in a graph database. Network analysis techniques have been applied to identify key structural properties of the web graph. Centrality measures, including degree, closeness, betweenness, and PageRank, have been used to determine the most important domains, while the Louvain algorithm has been applied to detect community structures. In addition, basic metadata statistics have been examined to provide a broader overview of the dataset. The results obtained from the custom crawler have been compared to data from the Common Crawl dataset. The comparison highlights how different data sources influence the observed network structure and the consistency of identified patterns. The thesis demonstrates how graph-based approaches can support the identification of influential domains and improve the understanding of large-scale web structures in practical applications.