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Preference learning by matrix factorization on island models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10380307" target="_blank" >RIV/00216208:11320/18:10380307 - isvavai.cz</a>

  • Result on the web

    <a href="http://ceur-ws.org/Vol-2203/146.pdf" target="_blank" >http://ceur-ws.org/Vol-2203/146.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Preference learning by matrix factorization on island models

  • Original language description

    This paper presents island models, methods, implementation and experiments connecting stochastic optimization methods and recommendation task (collaborative one). Our models and methods are based on matrix factorization. Parallel run of methods optimizes the RMSE metric from an island model point-of-view. This paper comments on architecture and some implementation decisions. We dealt with two research hypotheses. First, whether island models bring always improvement. We will show that almost always yes. Second, whether evolutionary algorithm does or does not always find the best solution. This will be confirmed only on smaller data. Experiments were provided on Movie Lens 100k and 1M data.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • 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 18th Conference Information Technologies - Applications and Theory (ITAT 2018)

  • ISBN

    978-1-72726-719-8

  • ISSN

    1613-0073

  • e-ISSN

    neuvedeno

  • Number of pages

    6

  • Pages from-to

    146-151

  • Publisher name

    CEUR Workshop Proceedings

  • Place of publication

    Košice, Slovakia

  • Event location

    Krompachy

  • Event date

    Sep 21, 2018

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article