All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Monotonization of User Preferences

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10319578" target="_blank" >RIV/00216208:11320/15:10319578 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-26154-6_3" target="_blank" >http://dx.doi.org/10.1007/978-3-319-26154-6_3</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-26154-6_3" target="_blank" >10.1007/978-3-319-26154-6_3</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Monotonization of User Preferences

  • Original language description

    We consider the problem of user-item recommendation as a multiuser instance ranking learning. A user-item preference is monotonizable if the learning can restrict to monotone models. A preference model is monotone if it is a monotone composition of rankings on domains of explanatory attributes (possibly describing user behavior, item content but also data aggregations). Target preference ordering of users on items is given by a preference indicator (e.g. purchase, rating). To increase intuitiveness, wefocus on a special class of monotone models which can be expressed as rules of generalized annotated programs. In this paper we focus on learning the (partial) order of vectors of rankings of user-item attribute values. We measure degree of agreement ofcomparable vec-tors with ordering given by preference indicators for each user. We are interested in distribution of this degree across users. We provide sets of experiments on user behavior data from an e-shop and on a subset of the sema

  • 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

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • 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 11th International Conference FQAS 2015

  • ISBN

    978-3-319-26154-6

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    29-40

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Krakov

  • Event date

    Oct 26, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article