About: Predicting Players Behavior in Games with Microtransactions

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ebooks.iospress.nl/volumearticle/37212
Description	This paper focuses on predicting player behaviour in two-player games with microtransactions. Typically the games are for free and companies generate their revenue by selling in-game goods. We show creation of a users behaviour model, which are then used in a recommendation system increasing in-game goods purchases. We focus on learning techniques in a novel way, predicting the time of purchases rather than the most likely product to be purchased. The player model is based on in-game signals, such as players success, curiosity, social interactions etc. We had access to a Pool Live Tour game dataset made by Geewa. We report promising results in predicting the purchase events. This paper focuses on predicting player behaviour in two-player games with microtransactions. Typically the games are for free and companies generate their revenue by selling in-game goods. We show creation of a users behaviour model, which are then used in a recommendation system increasing in-game goods purchases. We focus on learning techniques in a novel way, predicting the time of purchases rather than the most likely product to be purchased. The player model is based on in-game signals, such as players success, curiosity, social interactions etc. We had access to a Pool Live Tour game dataset made by Geewa. We report promising results in predicting the purchase events. (en)
Title	Predicting Players Behavior in Games with Microtransactions Predicting Players Behavior in Games with Microtransactions (en)
skos:prefLabel	Predicting Players Behavior in Games with Microtransactions Predicting Players Behavior in Games with Microtransactions (en)
skos:notation	RIV/68407700:21230/14:00218995!RIV15-MSM-21230___
http://linked.open...avai/riv/aktivita	S
http://linked.open...avai/riv/aktivity	S
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Šedivý, Jan Pluskal, Ondřej
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	38737
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/14:00218995
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Machine Learning; Feature Extraction; Online Games; Data Mining (en)
http://linked.open.../riv/klicoveSlovo	Data Mining Machine Learning Feature Extraction Online Games
http://linked.open...ontrolniKodProRIV	[84A419583B9C]
http://linked.open...v/mistoKonaniAkce	Praha
http://linked.open...i/riv/mistoVydani	Amsterdam
http://linked.open...i/riv/nazevZdroje	Frontiers in Artificial Intelligence and Applications
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Šedivý, Jan Pluskal, Ondřej
http://linked.open...vavai/riv/typAkce	EUR - Evropská
http://linked.open...ain/vavai/riv/wos	000350218400024
http://linked.open.../riv/zahajeniAkce	2014-08-18 (xsd:date)
issn	0922-6389
number of pages	10 (xsd:int)
http://bibframe.org/vocab/doi	10.3233/978-1-61499-421-3-230
http://purl.org/ne...btex#hasPublisher	IOS Press
https://schema.org/isbn	978-1-61499-420-6
http://localhost/t...ganizacniJednotka	21230

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