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Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.00 vteřin. 
Exploratory Analysis of Big Data in "jmenomesto"
 Trampeška, Václav ; Plchot, Oldřich (oponent) ; Landini, Federico Nicolás (vedoucí práce)
This thesis is concerned with the analysis of the database of the online game Jméno, město. In this game, players are tasked with adequately answering given categories with answers beginning with a given letter. The thesis analyzes the evolution of player behaviour over the lifetime of the game and the behaviour of players in different countries and cultures within the same and different languages based on the popularity of different answers. A web application was developed to facilitate the execution of these analyses, allowing easy-to-use data collection and data visualisation in charts without requiring knowledge of the database structure and a query language. The results of the proposed analysis methods are compared with Google Trends data to identify the similarities between the data observed in the game and internet searches. The comparison shows that the proposed methods can give meaningful results, and hence the database can be suitable for performing further specific analyses. Furthermore, partly based on the analysis results, the thesis proposes changes to improve the game in player experience and revenue generation.
Úplný záznam
Exploratory Analysis of Big Data in "jmenomesto"
 Trampeška, Václav ; Plchot, Oldřich (oponent) ; Landini, Federico Nicolás (vedoucí práce)
This thesis is concerned with the analysis of the database of the online game Jméno, město. In this game, players are tasked with adequately answering given categories with answers beginning with a given letter. The thesis analyzes the evolution of player behaviour over the lifetime of the game and the behaviour of players in different countries and cultures within the same and different languages based on the popularity of different answers. A web application was developed to facilitate the execution of these analyses, allowing easy-to-use data collection and data visualisation in charts without requiring knowledge of the database structure and a query language. The results of the proposed analysis methods are compared with Google Trends data to identify the similarities between the data observed in the game and internet searches. The comparison shows that the proposed methods can give meaningful results, and hence the database can be suitable for performing further specific analyses. Furthermore, partly based on the analysis results, the thesis proposes changes to improve the game in player experience and revenue generation.
Úplný záznam

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