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Katchabaw, Mike
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1

Understanding Players and Play Through Game Analytics:

, In: Studies in Big Data; Applied Data Science,
Tan, Jonathan ; Katchabaw, Mike ; Slogar, Damir - p. 101-115 , 2023
Link: https://doi.org/10.1007/..
 
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2

A Reusable Methodology for Player Clustering Using Wasserst..:

, In: Entertainment Computing – ICEC 2022; Lecture Notes in Computer Science,
Tan, Jonathan ; Katchabaw, Mike - p. 296-308 , 2022
Link: https://doi.org/10.1007/..
 
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3

Proceedings of the 2008 Conference on Future Play: Research..:

Kapralos, Bill ; Katchabaw, Mike ; Rajnovich, Jay , 2008
Link: https://dl.acm.org/doi/1..
 
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4

Proceedings of the 2007 conference on Future Play:

Kapralos, Bill ; Katchabaw, Mike ; Rajnovich, Jay , 2007
Link: https://dl.acm.org/doi/1..
 
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5

A Reusable Scripting Engine for Automating Cinematics and C..:

McLaughlin, Matt ; Katchabaw, Mike
https://journals.sfu.ca/loading/index.php/loading/article/view/16/8.  , 2007
Link: https://journals.sfu.ca/..
 
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6

Automating Content Analysis of Video Games:

Bullen, Terry ; Katchabaw, Mike ; Dyer-Witheford, Nick
https://journals.sfu.ca/loading/index.php/loading/article/view/5/2.  , 2007
Link: https://journals.sfu.ca/..
 
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7

Team Sports for Game AI Benchmarking Revisited:

Mozgovoy, Maxim ; Preuss, Mike ; Bidarra, Rafael.
International Journal of Computer Games Technology.  2021 (2021)  - p. 1-9 , 2021
Link: https://doi.org/10.1155/..
 
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