Sequential group recommendations based on satisfaction and disagreement scores

Maria Stratigi, Evaggelia Pitoura, Jyrki Nummenmaa, Kostas Stefanidis

Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

12 Sitaatiot (Scopus)
15 Lataukset (Pure)

Abstrakti

Recently, group recommendations have gained much attention. Nevertheless, most approaches consider only one round of recommendations. However, in a real-life scenario, it is expected that the history of previous recommendations is exploited to tailor the recommendations towards meeting the needs of the group members. Such history should include not only which items the system suggested, but also the reaction of the members to these items. This work introduces the problem of sequential group recommendations, by exploiting the concept of satisfaction and disagreement. Satisfaction describes how well the group received the suggested items. Disagreement describes the satisfaction bias among the group members. We utilize these concepts in three new aggregation methods, SDAA, SIAA and Average+, designed to address the specific challenges introduced by sequential group recommendations. We experimentally show the effectiveness of our methods using big real datasets for both stable and ephemeral groups.

AlkuperäiskieliEnglanti
Sivut227–254
JulkaisuJournal of Intelligent Information Systems
Vuosikerta58
Numero2
Varhainen verkossa julkaisun päivämäärä14 heinäk. 2021
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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