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Understanding Transparent and Complicated Users as Instances of Preference Learning for Recommender Systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10319658" target="_blank" >RIV/00216208:11320/16:10319658 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Understanding Transparent and Complicated Users as Instances of Preference Learning for Recommender Systems

  • Original language description

    In this paper we are concerned with user understanding in content based recommendation. We assume having explicit ratings with time-stamps from each user. We integrate three different movie data sets, trying to avoid features specific for single data and try to be more generic. We use several metrics which were not used so far in the recommender systems domain. Besides classical rating approximation with RMSE and ratio of order agreement we study new metrics for predicting Next-k and (at least) 1-hit at Next-k. Using these Next-k and 1-hit we try to model display of our recommendation - we can display k objects and hope to achieve at least one hit. We trace performance of our methods and metrics also as a distribution along each single user. We define transparent and complicated users with respect to number of methods which achieved at least one hit. We provide results of experiments with several combinations of methods, data sets and metrics along these three axes.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA15-19877S" target="_blank" >GA15-19877S: Automated Knowledge and Plan Modeling for Autonomous Robots</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

    Mathematical and Engineering Methods in Computer Science

  • ISBN

    978-3-319-29816-0

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    23-34

  • Publisher name

    Springer

  • Place of publication

    Berlín

  • Event location

    Telč

  • Event date

    Oct 23, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article