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Predicting Time of Purchase in Games with Microtransactions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00301375" target="_blank" >RIV/68407700:21230/16:00301375 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Predicting Time of Purchase in Games with Microtransactions

  • Original language 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 focus on modeling the recommendation system 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 created a model based on regressing the time before purchase using machine learning. We report promising results in predicting the time of purchase events.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 20th International Scientific Student Conferenece POSTER 2016

  • ISBN

    978-80-01-05950-0

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    1-5

  • Publisher name

    Czech Technical University in Prague

  • Place of publication

    Praha

  • Event location

    Praha

  • Event date

    May 24, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article